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About the job
We are building a technical team to develop software solutions in the medical field. We are looking for specialists who want to work in a small team, making a direct impact on the product, with a strong focus on quality, data security, and scientific rigor.

OPEN POSITIONS:

1. Technical Lead

-Technical coordination of the team, system and data flow architecture, planning and tracking deliverables, quality assurance

-Over 5 years of experience in developing artificial intelligence / machine learning systems (target range: 5–10 years)

-Technical team leadership experience; Python, PyTorch, or TensorFlow

2. Machine Learning / Data Science Expert

-Dataset preparation, model development and training, statistical validation, and error analysis

-Minimum 2 years of experience in machine learning / data science

-Python (pandas, scikit-learn, PyTorch, or TensorFlow), solid knowledge of statistics

3. Computer Vision Expert

-Development and training of deep learning models on image data, quality control of image datasets, performance evaluation

-Minimum 2 years of experience in computer vision / deep learning

-Python, PyTorch or TensorFlow, OpenCV

4. Full-stack / Mobile Software Developer

-iOS and Android mobile applications, backend services and APIs, API integrations, data security and protection (GDPR)

-Minimum 2 years of experience in software development

-Native or Flutter / React Native; Python, Node.js, or Java; cloud services (AWS or Google Cloud)

Mandatory Requirements (All Positions)

-University degree in the field (Computer Science, Computer Engineering, Engineering, Mathematics-Informatics, Bioinformatics, or similar)

-Professional working proficiency in English

Nice to Have

-Master's or Ph.D. degree in the field

-Experience in R&D (Research & Development) projects

-Experience with regulated software (e.g., IEC 62304)

What We Offer

-Attractive compensation package, commensurate with experience

-24-month employment contract

-Full-time or part-time options compatible with other professional commitments

-100% remote work

-Direct impact on the product and a genuine research component

-Bachelor's degree (as listed)

Role Overview

We are looking for an AI Automation Engineer with experience building LLM-powered content workflows, marketing automation pipelines, and SEO/AEO systems.

This role will work alongside the Senior Forward Deployed Engineer to operationalize an existing library of AI-powered marketing skills and develop an automated content pipeline that supports an agentic website.

The ideal candidate combines strong Python/API integration experience with a practical understanding of SEO, Answer Engine Optimization (AEO), and content publishing workflows.
This is a technical engineering role, not a traditional content marketing or SEO strategist position.

Key Responsibilities

AI Skill & Workflow Integration
• Review and operationalize existing AI marketing skills, prompts, and configurations.
• Adapt existing workflows to work with a shared marketing knowledge repository.
• Implement reusable agent workflows for keyword research, content briefs, content generation, and validation.
• Integrate LLM-based processing with existing tools and APIs.
• Establish error handling, workflow monitoring, and quality controls.

SEO/AEO Content Engine
• Develop an automated SEO/AEO content pipeline supporting keyword research, content planning, generation, optimization, and publishing.
Integrate existing SEO/AEO skills into executable workflows.
• Implement content validation processes, including metadata, internal linking, structured data, and SEO best practices.
• Support content formatting and publishing into the website's CMS.
• Implement human-review and approval steps before publication.
• Help prepare an initial batch of launch-ready SEO/AEO content.

Integration & Automation
• Build API integrations between AI workflows, marketing repositories, and website publishing infrastructure.
• Support automated content deployment and publishing.
• Collaborate with the FDE to ensure content schemas and workflow outputs are compatible with the website.
• Create clear documentation for maintaining and extending the automation workflows.

Required Technical Skills
• Strong Python development skills, including API integrations and workflow automation.
• Experience using LLM APIs, prompt engineering, and structured AI outputs.
• Hands-on experience building AI automation pipelines or agent-based workflows.
• Familiarity with Git repositories, JSON/YAML configurations, and reusable prompt/skill libraries.
• Working knowledge of technical SEO, AEO, structured data, metadata, and content optimization.
• Experience integrating CMS platforms and content publishing APIs.
• Familiarity with workflow orchestration tools, scheduling, logging, and error handling.
• Ability to work independently with existing technical documentation and reusable components.

Preferred Qualifications
• Experience with LangGraph, n8n, or similar automation frameworks.
• Familiarity with Next.js, Sanity, Contentful, or comparable headless CMS platforms.
• Experience with programmatic SEO, AI-assisted content generation, or content automation platforms.
• Knowledge of SEO research tools and search analytics.
• Experience building reusable AI agents or marketing automation systems.

Expected Deliverables
• Operational SEO/AEO agent workflows using the existing marketing skill library.
• Automated keyword research, content planning, and generation pipeline.
• Content quality validation and approval workflows.
Integration with website CMS and publishing infrastructure.
• Initial launch-ready content batch, subject to customer editorial approval.
• Documentation and operational handoff for ongoing automation.

I’m streamlining the way my Android phone and Mac workstation talk to each other and I need an automation-minded assistant to help me build a reliable, end-to-end pipeline.

Here’s what I’m aiming for:
• Ecosystem integration across both devices so photos, videos, and project files land in the right place without manual drag-and-drop.
• File automation that watches specific folders, triggers conversions or renames, and pushes everything into an organised archive.
• A small-footprint local AI configuration (think lightweight tagging or smart sorting models running on-device).
• Music-distribution logistics, including prepping releases with DistroKid-ready metadata, artwork, lyric sheets, and multi-format audio/video assets.

Acceptance criteria
• New media captured on Android appears on my Mac within minutes, preserving original timestamps.
• Selected folders stay bi-directionally in sync even if I’m offline for a while.
• Media is auto-sorted into a date / project hierarchy, converted to preferred production formats, and safely backed up.
• Music assets export with correct DistroKid metadata rules and a repeatable folder structure for songs, artwork, and videos.
• The entire workflow can be reproduced from a documented script or step-by-step guide.

In your proposal, focus on previous projects done with this scope and outline your experience level in each area—cross-device syncing, automation scripting (e.g. Hazel, Automator, Shortcuts, Tasker, SyncThing, rsync, cron), and music-release pipelines. A short plan of attack or demo clip of a similar setup will help me pick quickly.

Skills: Python, Audio Services, Android, Windows Mobile, Mac OS, Automation, AI Automation, iOS

Redesign our existing Xero invoice template to match our preferred layout and format.

Add a new text field/column called "Authorisation Code" where we can manually enter a unique number or code for each invoice.

The payment code must appear on the final invoice when printed, downloaded as a PDF, or emailed to customers.

The payment code should be editable for each invoice.

Keep all existing invoice details, including customer information, description, quantity, price and totals.

Ensure the customised template works correctly within Xero.

Important: We want the payment code to be entered directly when creating or editing an invoice in Xero, rather than manually editing the PDF afterwards.

Please confirm whether this is possible within Xero and explain how you would implement it.

We are looking for someone with experience in Xero custom invoice templates and advanced DOCX template customisation.

Please provide your quotation and estimated completion time.

We’re looking for a Python developer to build a practical internal tool that helps our team make better Amazon advertising decisions and improve profitability.

The tool will analyze advertising performance alongside product costs and inventory, identify opportunities to reduce wasted spend, and generate recommendations for our team to review.

What we’re looking for:
* Strong Python and SQL skills.
* Experience building data-driven applications or business automation tools.
* Experience working with APIs and structured datasets.
* Ability to build, test, and document reliable software.

Experience with Amazon PPC, e-commerce analytics, or advertising optimization is a plus.

We prefer a hands-on developer who can explain their work and deliver a maintainable solution. The project will begin with a focused initial scope, with potential for further development.

To apply, please share:

1. A similar software tool or automation system you have personally built.
2. Your experience with Amazon PPC, bid optimization, advertising performance, or e-commerce data.
3. How would you build an initial tool that identifies wasted ad spend and recommends more profitable Amazon PPC bids?

We need a senior developer to add new features to an existing multi-tenant SaaS application. The work includes building tenant-specific functionality, improving the user experience, and supporting ongoing product development. You should be comfortable working in a fast-paced environment, collaborating with stakeholders, and delivering reliable, scalable solutions. Experience with SaaS architecture and feature implementation is important for success in this role.

Role Overview

We are looking for a Senior Forward Deployed Engineer to lead the development of an AI-enabled Marketing Operating System (MarketingOS) and an agentic website for an early-stage technology company.

This is a hands-on engineering role requiring strong full-stack development experience, AI/LLM integration capabilities, and experience building production-ready applications.

The engineer will work directly with the customer's marketing leadership to translate business requirements into a practical technical architecture and deliver a functioning MVP.

Key Responsibilities

Architecture & MarketingOS Infrastructure
• Design and implement the technical architecture for the MarketingOS, including shared configuration, skills, prompts, and agent execution frameworks.
• Establish shared GTM/brand knowledge repositories and separate functional repositories for Marketing, Sales, and Customer Success.
• Operationalize existing AI skills and workflows rather than rebuilding them from scratch.
Integrate agent workflows with CRM, CMS, and external tools through APIs.
• Implement version control, deployment processes, security, and operational guardrails.

Agentic Website Development
• Recommend and implement a modern website architecture using technologies such as Next.js, React, TypeScript, Vercel, Cloudflare, and a headless CMS.
• Build reusable website components and a structured content/block system using customer-provided designs.
• Develop homepage, product, solution, resource, and landing page templates.
• Implement dynamic, account-level content personalization based on recognized organizations, without individual visitor tracking.
• Integrate website functionality with the MarketingOS and applicable CRM systems.
• Ensure the website meets performance, accessibility, security, and SEO technical requirements.

AI & Agent Integration
• Implement LLM-based workflows, agent configurations, tools, and reusable execution patterns.
• Build integrations between existing AI skill libraries and application services.
• Establish appropriate validation, observability, testing, and human-review guardrails.
• Support the integration of automated content generation and publishing workflows.

Required Technical Skills
• Strong full-stack development experience with TypeScript, JavaScript, React, and Next.js.
• Experience building production web applications using modern cloud hosting and deployment platforms.
• Hands-on experience with LLM APIs, AI agents, tool calling, prompt orchestration, and structured outputs.
• Strong understanding of REST APIs, webhooks, integrations, and data models.
• Experience with Git-based repositories, CI/CD pipelines, and infrastructure configuration.
• Experience integrating headless CMS platforms such as Sanity, Contentful, or similar.
• Familiarity with Python for AI workflows and backend automation.
• Ability to independently recommend architecture, make technical decisions, and deliver working solutions.

Preferred Qualifications
• Experience with AI agent frameworks such as LangGraph or similar orchestration tools.
• Experience with AWS Bedrock, Anthropic, OpenAI, or comparable LLM platforms.
• Knowledge of account-based personalization and marketing technology integrations.
• Experience implementing technical SEO, structured metadata, and content publishing systems.
• Prior experience working directly with startup founders or business stakeholders.

Expected Deliverables
• Working MarketingOS repository and agent infrastructure.
• Operational shared canon and functional skill repositories.
• Production-ready MVP website with reusable content components.
• Account-level personalization and approved CRM/tool integrations.
• Integrated AI workflows with security and validation guardrails.
• Architecture documentation, deployment configuration, and technical handoff.

Summary
SIEM Security Engineer – French or Dutch (Brussels Onsite)

Summary

Location: Brussels, Belgium
Work Mode: On-site
Employment Type: Full-time
Experience: 8–15 Years
Mandatory: Fluent French or Dutch (one language is enough)

About the Opportunity

We are seeking an experienced SIEM Security Engineer, fluent in French or Dutch, with strong Elastic Security expertise. You will build and operate an Elastic Security (SIEM) platform, integrate threat intelligence, monitor cloud environments and deliver actionable security insights in a collaborative, cybersecurity-focused team.

Key responsibilities

-Design, manage, configure and optimise the Elastic Security (SIEM) platform to collect and correlate security event data.
-Collaborate with the team to create and maintain security solutions based on Elasticsearch.
-Integrate threat intelligence feeds into the SIEM and Elasticsearch for proactive threat hunting.
-Perform regular platform upgrades, ensuring scalability and reliability.
-Monitor security logs, alerts and reports to identify issues and anomalies in cloud environments.
-Use Elasticsearch to index and search security-related data for analysis and reporting.

Required qualifications:

-Proven experience as a security engineer focusing on SIEM and the Elastic stack (Kibana, Logstash, Kafka).
-Strong expertise in Elasticsearch, including indexing, querying and visualisation.
-Proficiency in scripting/programming languages such as Python or ES|QL for automation.
-Experience integrating logs in cloud environments such as AWS and Azure.
-Excellent problem-solving skills and ability to work under pressure in incident response scenarios.
-Fluent in French or Dutch (one language is enough).

Nice to have:

-Knowledge of cybersecurity frameworks and standards (SOC 2, ISO 27001).
-Familiarity with Kubernetes and other cloud-native technologies.
-Experience with Windows and Linux endpoint security and EDR solutions.

Role Overview

We are looking for a Senior Forward Deployed Engineer to lead the development of an AI-enabled Marketing Operating System (MarketingOS) and an agentic website for an early-stage technology company.

This is a hands-on engineering role requiring strong full-stack development experience, AI/LLM integration capabilities, and experience building production-ready applications.

The engineer will work directly with the customer's marketing leadership to translate business requirements into a practical technical architecture and deliver a functioning MVP.

Key Responsibilities

Architecture & MarketingOS Infrastructure
• Design and implement the technical architecture for the MarketingOS, including shared configuration, skills, prompts, and agent execution frameworks.
• Establish shared GTM/brand knowledge repositories and separate functional repositories for Marketing, Sales, and Customer Success.
• Operationalize existing AI skills and workflows rather than rebuilding them from scratch.
Integrate agent workflows with CRM, CMS, and external tools through APIs.
• Implement version control, deployment processes, security, and operational guardrails.

Agentic Website Development
• Recommend and implement a modern website architecture using technologies such as Next.js, React, TypeScript, Vercel, Cloudflare, and a headless CMS.
• Build reusable website components and a structured content/block system using customer-provided designs.
• Develop homepage, product, solution, resource, and landing page templates.
• Implement dynamic, account-level content personalization based on recognized organizations, without individual visitor tracking.
• Integrate website functionality with the MarketingOS and applicable CRM systems.
• Ensure the website meets performance, accessibility, security, and SEO technical requirements.

AI & Agent Integration
• Implement LLM-based workflows, agent configurations, tools, and reusable execution patterns.
• Build integrations between existing AI skill libraries and application services.
• Establish appropriate validation, observability, testing, and human-review guardrails.
• Support the integration of automated content generation and publishing workflows.

Required Technical Skills
• Strong full-stack development experience with TypeScript, JavaScript, React, and Next.js.
• Experience building production web applications using modern cloud hosting and deployment platforms.
• Hands-on experience with LLM APIs, AI agents, tool calling, prompt orchestration, and structured outputs.
• Strong understanding of REST APIs, webhooks, integrations, and data models.
• Experience with Git-based repositories, CI/CD pipelines, and infrastructure configuration.
• Experience integrating headless CMS platforms such as Sanity, Contentful, or similar.
• Familiarity with Python for AI workflows and backend automation.
• Ability to independently recommend architecture, make technical decisions, and deliver working solutions.

Preferred Qualifications
• Experience with AI agent frameworks such as LangGraph or similar orchestration tools.
• Experience with AWS Bedrock, Anthropic, OpenAI, or comparable LLM platforms.
• Knowledge of account-based personalization and marketing technology integrations.
• Experience implementing technical SEO, structured metadata, and content publishing systems.
• Prior experience working directly with startup founders or business stakeholders.

Expected Deliverables
• Working MarketingOS repository and agent infrastructure.
• Operational shared canon and functional skill repositories.
• Production-ready MVP website with reusable content components.
• Account-level personalization and approved CRM/tool integrations.
• Integrated AI workflows with security and validation guardrails.
• Architecture documentation, deployment configuration, and technical handoff.

I want to log into a site everyday and complete a task once logged into the site.

Data Engineer, Sports Data & Pipelines

We’re looking for a strong Data Engineer to help expand the data infrastructure for a sports analytics company.

The main focus is building and maintaining reliable data pipelines, but we also need someone who is comfortable working directly with the data - cleaning it, structuring it, combining sources, and creating high-quality datasets for analysis and modeling.

### What You’ll Do

- Build and maintain Python data pipelines
- Connect to APIs, databases, feeds, and other data sources
- Collect historical and real-time sports data
- Clean, normalize, validate, and structure raw data
- Combine multiple data sources into usable datasets
- Create research-ready datasets for our team
- Investigate missing, inconsistent, or incorrect data
- Monitor pipelines and fix issues when feeds break or change
- Add new sports, leagues, and data sources over time

### What We’re Looking For

- Strong Python and SQL
- Experience building production data pipelines
- Strong data cleaning and data-wrangling skills
- Experience with ETL pipelines
- Comfortable working with APIs, JSON, WebSockets, and databases
- Experience with Airflow or similar workflow tools
- Strong Pandas skills
- Able to turn messy raw data into clean, usable datasets
- Comfortable with basic data analysis and exploratory work
- Able to work independently and take ownership of projects

Experience working with sports data is a strong plus.

Experience with basketball data is especially valuable, including NBA or college basketball data such as play-by-play, box scores, lineups, player data, and real-time game feeds.

### Location & Collaboration

We are primarily looking for candidates based in **North America or Europe**.

Strong professional English is required, along with regular overlap with North American working hours for team communication and collaboration.

### When Applying

Please keep your response short and answer:

1. Tell us about one data pipeline you personally built.
2. Give an example of a messy dataset you cleaned and structured for analysis.
3. Have you worked with sports or basketball data before?
4. Have you worked with real-time APIs, WebSockets, or live data feeds?

Please include links to relevant work or GitHub if available.

Reddit Growth Specialist & Automation Lead (Outreach, Social Listening & Lead Gen)

About Kornerz
Kornerz is an ad-free, moderated digital network designed for authentic human connection, meaningful conversation, and thinkers tired of algorithmic noise, doomscrolling, and surface-level social media.

Role Overview
Reddit is our highest-converting customer acquisition channel. We are seeking a growth hacker, community outreach specialist, or automation engineer who can identify high-intent Reddit posts and conduct proactive, high-volume engagement to drive app downloads, signups, and active subscribers.

You will identify users experiencing digital burnout, loneliness, or frustration with mainstream platforms (e.g., looking for real friends, tired of Instagram/TikTok algorithms, seeking niche community hubs) and introduce them to Kornerz via contextual public comments and direct messages (DMs).

Core Responsibilities
Social Listening & Keyword Monitoring: Monitor relevant subreddits (e.g., r/FindAFriend, r/socialskills, r/nosurf, r/digitalminimalism, r/lonely, and related niche communities) using automated social listening scrapers or monitoring tools.
Mass Outreach & Engagement: Scale our direct outreach to handle thousands of high-converting, compliant touchpoints per month across DMs and public thread interactions.
Conversational Copywriting: Draft authentic, non-spammy outreach templates and comment replies that provide genuine value, address the user's specific pain point, and introduce Kornerz naturally.
Account Safety & Infrastructure: Maintain high Reddit deliverability, manage accounts responsibly, adhere strictly to Reddit’s community guidelines, and prevent shadowbans or domain flagging.
Conversion Tracking & Optimization: Track link clicks, app store referrals, and signup conversion rates to continuously improve response rates.

Candidate Qualifications & Capabilities
We are open to either an experienced manual outreach team or a technical growth hacker with an automated/semi-automated system (human-in-the-loop):
Proven track record running cold outreach, social listening, or lead generation campaigns on Reddit.
Experience using tools such as Reddit API, Python/PRAW, Zapier, Make, F5Bot, Syften, Brand24, or custom social scrapers.
Strong understanding of Reddit culture: how to engage authentically without triggering community backlash or moderator bans.
Ability to set up conversion tracking (UTM parameters, custom redirect URLs, attribution).
Deliverables & KPIs
Target Volume: 25.000+ targeted, high-intent engagements/messages per month.
Weekly Reporting: Active leads contacted, reply/engagement rate, click-throughs, and completed Kornerz signups.
Outreach Playbook: Documented keyword filters, monitored subreddit lists, and high-performing message scripts.
How to Apply
In your proposal, please answer the following:
Methodology: Would you execute this via automated tools/scripts, manual outreach assistants, or a hybrid approach?
Reddit Safety: How do you handle Reddit rate limits, anti-spam filters, and subreddit-specific rules to protect our brand's reputation?
Relevant Experience: Share a brief example or case study of a past Reddit growth or outbound outreach campaign you executed.
Include the word "Kornerstone" at the very top of your application so we know you read this posting thoroughly.

# Need Help Improving an AI Assistant Connected to My App — OpenAI / Python

Hi,

I'm working on a small personal project and looking for an experienced developer to help me improve my AI assistant.

I already have an existing application built with Python, FastAPI, PostgreSQL, React, and the OpenAI API.

**What I'm trying to achieve:**

I want the AI assistant to have natural conversations while intelligently using information already stored in my application.

For example:

- The assistant should understand what the user is asking, including complex questions and follow-ups.
- It should be able to retrieve relevant information from the user's saved records, documents, and previous interactions.
- If the information is already available, it shouldn't ask the user for it again.
- If something is missing or unclear, it should ask a relevant follow-up question.
- It should understand multiple topics within the same conversation.
- It should maintain context across messages and sessions.
- It should provide clear, natural answers based on the available information.
- It should respect user permissions and avoid making up missing information.

**The technical side:**

I already have a backend, database, structured data, and some conversational AI code.

I need help connecting these components properly using OpenAI Responses API, function calling, and good conversation management.

I'm not looking to rebuild everything or introduce a complicated new architecture. I'd prefer to improve and reuse what I already have.

**Budget:**

My budget is limited, so I'd like to start with a small, fixed-price task to review the existing implementation and identify what needs improvement.

If things go well, we can work on the improvements step by step.

If you have experience building context-aware AI assistants connected to existing applications, please let me know.

I'd also appreciate a couple of examples of similar work you've done and your approximate rate.

Thanks!

About the Role

We are hiring a Senior Full-Stack Engineer to become one of the strongest technical contributors on the team.

The single most important thing we’re looking for is experience scaling a SaaS product. We want someone who has already seen what happens as a live platform grows: increasing complexity, technical debt, scaling bottlenecks, evolving data models, unreliable integrations, and engineering decisions that worked at one stage but became expensive at the next.

This is a hands-on senior engineering role with strong technical leadership expectations. You will design and write production code, own substantial systems end to end, influence architectural decisions, challenge technical direction when needed, and raise the engineering level of the people around you.


Project

FinTech SaaS platform built for the restaurant and hospitality industry. Our products handle tip pooling and payouts, payroll, reporting and compliance, labor and operational data, and integrations with the systems hospitality businesses already use. The platform is live, serves thousands of customers and moves millions of dollars.


Required Hard Skills

- Several years operating at Senior Engineer level on a SaaS product that grew significantly while you were there. You have seen a system become meaningfully bigger and understand the problems that tend to arrive next.
- Strong Python and Django / Django REST Framework experience, or deep experience in a closely comparable backend stack. We also welcome candidates with strong backend experience in other programming languages and frameworks.
- Strong React and TypeScript experience, with the ability to work effectively across backend and frontend when required.
- Strong PostgreSQL and data modeling skills. You should be comfortable designing schemas that can evolve as the business grows into new products and safely changing them once they contain production data.
- Production experience with asynchronous and distributed workloads using Celery or comparable technologies.
- Strong understanding of API design and third-party integrations, including failure handling, retries, idempotency, data consistency, reconciliation, and situations where the system on the other side is unreliable or outside your control.
- Strong understanding of software architecture and the ability to make pragmatic architectural decisions inside a large existing codebase rather than only designing systems from scratch.
- Experience identifying and addressing performance, scalability, reliability, and maintainability problems before they become critical.
- Strong testing practices and experience safely evolving systems that must remain operational while they are being changed.
- Production experience with Docker, CI/CD, monitoring, error tracking, and observability.
Strong Linux knowledge.
- Sound judgment about technical debt: knowing the difference between an acceptable shortcut and one that will create significant problems later, and being able to improve a system while it remains in production.
- Everyday experience with using AI agents for work (Claude Code or Codex). Familiar with configuring AI toolset, understanding pros and cons of modern AI.


Current Stack

Django / DRF, PostgreSQL, Redis, Celery, Docker, Traefik, Datadog, Sentry, Mailgun, GitHub Workflows.
Next.js, MUI, TanStack Query, React Hook Form, Zod, Vitest.

Nice to Have

- FinTech or financial systems experience, particularly payments, payouts, ledgers, reconciliation, payroll, banking, audit trails, or other systems where financial correctness matters.
- Experience with restaurant or hospitality technology, including POS, scheduling, workforce management, payroll, or similar systems.
- Experience with high-volume or business-critical third-party integrations.
- Experience improving a system with meaningful legacy code or technical debt while the product remained actively developed.
- Experience with multi-tenant SaaS architectures.
- Experience improving engineering practices across a team rather than only within your own work.
- Experience as a Senior Engineer in a company of roughly 20–200 people, where your role included helping decide what technical work actually mattered.


Required Soft Skills

- Ability to take technical ownership beyond your own tickets and think about the health of the product and engineering system as a whole.
- Strong engineering judgment and the confidence to challenge technical decisions constructively, including decisions made by Staff Engineers and engineering leadership.
- Comfort with ambiguity. Problems will not always arrive fully specified, and part of your job is asking the questions that make them clear before code gets written.
- Ability to explain complex technical trade-offs clearly to engineers, Product, and non-technical stakeholders.
- A strong teaching mindset. You explain your reasoning, document important decisions, review code seriously, and make the engineers around you better rather than becoming the only person who understands a difficult system.
- Comfortable taking leadership during difficult technical situations without waiting for someone else to define every step of the solution.
- Strong written communication and self-direction. The team is distributed across Canada and Europe with limited live overlap, so you need to communicate clearly asynchronously and drive your own work.
- Fluent English, written and spoken.


Key Responsibilities

1. Own substantial systems end to end

Take meaningful problems that have been identified but not fully solved and work with Staff Engineers and Product to determine the right technical approach.
Own complex initiatives from problem definition through design, implementation, migration, testing, rollout, and production monitoring.
Design not only for the expected path, but also for what happens when something goes wrong in production.
Remain responsible for the systems you build once they are carrying real customer data and real money.

2. Help strengthen the architecture of a growing product

Work closely with Staff Engineers and the VP of Engineering on architectural decisions and technical direction.
Understand the existing architecture and identify where today’s decisions may create tomorrow’s problems.
Identify areas where the platform may struggle as product complexity, integrations, customers, data volume, and transaction volume increase.
Challenge architectural decisions constructively when you see a better approach.
Help evolve the architecture incrementally through small, safe improvements rather than unnecessary rewrites or over-engineering.

3. Protect correctness, reliability, and engineering quality

Treat financial correctness as a first-class engineering concern.
Design for reconciliation and auditability: how we prove a number is correct, understand how it was produced, and detect discrepancies before customers do.
Use Datadog, Sentry, logs, production data, and other signals to identify recurring problems and their root causes.
Improve observability, error handling, testing, deployment safety, performance, and operational reliability.
Make sure recurring production problems are solved systematically rather than repeatedly patched.

4. Own technically difficult areas of the product

Lead work involving complex third-party integrations, asynchronous workflows, data synchronization, reconciliation, migrations, and failure recovery.
Design systems that behave predictably when external APIs fail, requests are duplicated, jobs execute late, or data arrives in an unexpected state.
Work closely with Product to make technical feasibility and engineering constraints visible before implementation begins.
Help break large technical initiatives into safe, incremental pieces that can be built, migrated, and released without unnecessarily putting the existing platform at risk.


5. Make the case for important technical work

Identify technical debt, platform investment, reliability work, and architectural improvements that may not naturally appear on the product roadmap.
Distinguish between debt that can safely remain and debt that is materially affecting reliability, engineering speed, or future product development.
Make the business and technical case for that work using evidence rather than engineering preference alone.
Help sequence improvements so they support product development rather than competing with it unnecessarily.

6. Raise the level of the engineering team

Be a strong technical reference point for other engineers.
Review architecture, designs, and pull requests with a focus on correctness, reasoning, and long-term maintainability.
Explain why you would make a decision differently rather than simply leaving a verdict.
Mentor engineers through reviews, pairing, technical discussions, and example.
Document important knowledge and decisions so understanding stays with the team rather than with one individual.
Take leadership when a difficult technical problem crosses multiple areas or engineers.


7. Remain hands-on

Design and write production code across the backend and frontend.
Take direct ownership of technically difficult or risky work when appropriate.
Debug difficult production issues and establish their root causes.
Read and understand the existing codebase before changing it.
Build enough direct knowledge of the platform to ensure your technical decisions are grounded in how the system actually works.


Who this position is not for

This is not a role for someone whose definition of seniority is simply delivering more complicated tickets.
If you prefer receiving clearly defined tickets and technical solutions and then implementing them, this role will probably be frustrating.
It is not a management role. You won’t have direct reports or headcount responsibility. Leadership here comes through technical ownership, judgment, mentoring, reviews, and influence.
It is also not a Staff Engineer role. Our Staff Engineers and VP of Engineering set the overall technical direction and architecture. You will help shape that direction, challenge it when needed, and fully own the design and implementation of substantial systems within it.
It is not a greenfield role. You will be joining a live platform with thousands of customers and a roadmap that does not pause while technical improvements are made. Much of the work involves understanding existing systems, migrating them safely, and improving them incrementally rather than replacing them.
If you naturally ask what happens when the system gets significantly larger, how it fails, how we know the data is correct, and what today’s shortcut will cost us a year from now, you’ll recognize the work.


Things You Should Know Before Applying

This position is open to individual candidates only. We do not consider agencies, outsourcing companies, or third-party service providers.
The engineering challenge is no longer simply building features quickly. It is continuing to ship while improving reliability, scalability, architecture, and the technical foundation required for significant year-over-year growth.
There is technical debt. Part of your job is determining which debt actually matters, making its impact visible, and helping address it without stopping product development.
Requirements will sometimes be incomplete. We expect you to help shape the solution rather than wait for perfect specifications.
You will be expected to disagree when necessary, propose better approaches, and explain the reasoning behind them.

We are looking for a Back-End Developer to create a file processing and document conversion service. This service will enable our digital products and web applications to accept files, process them in the background, convert them to supported formats, and make the completed files available for download. The project focuses on establishing a reliable back-end service that handles document processing tasks, including file uploads, format validation, conversion requests, processing queues, job tracking, and secure file storage. The service will offer a consistent set of APIs that other applications can use to submit files, monitor processing progress, retrieve results, and manage completed jobs. You will be responsible for designing and implementing the back-end architecture, integrating appropriate file-processing tools, managing asynchronous tasks, and ensuring that files are handled securely and efficiently. The service should also be structured to support additional file formats and processing capabilities as our digital products evolve.

Key responsibilities for this position include:

- Develop the core architecture for a file processing service that supports file submission, processing requests, job management, and result retrieval.

- Build secure API endpoints that accept supported file uploads, validate request data, enforce file-size limits, and return appropriate responses.

- Verify file types, extensions, MIME types, and other relevant properties before processing. Reject unsupported, malformed, or potentially unsafe files.

- Integrate suitable processing libraries or conversion tools to support agreed formats, such as converting DOCX documents to PDF or extracting text from supported document files.

- Use background workers and a task queue to process files without keeping API requests open for the entire conversion process.

- Create functionality for tracking processing jobs through statuses such as queued, processing, completed, and failed, with relevant timestamps and error information.

- Connect the service to an appropriate storage solution for uploaded files and generated outputs, including file references, access controls, and retention rules.

- Develop endpoints that allow authorized users or connected applications to check job status and retrieve completed files through controlled download mechanisms.

- Implement appropriate timeout handling, retry policies, cleanup procedures, and error reporting for failed or interrupted processing tasks.

- Protect against unauthorized access, unsafe file uploads, path traversal, excessive resource consumption, and accidental exposure of sensitive documents.

- Implement sensible concurrency limits, file-size restrictions, and resource-management practices to prevent large or complex documents from overwhelming the service.

- Write automated tests, document API contracts and supported formats, and provide setup and integration instructions for other developers.

I want to build a modern website where people can discover events, buy tickets online, and connect with event organizers.

The idea is similar to Eventbrite, or other event platforms. I want something professional, easy to use, visually appealing, and accessible on both mobile phones and computers.

I am not a technical person, so I need a developer who can understand my vision, recommend the best approach, and handle the entire process from design to launch.

What I Want the Website to Do

1. Event Discovery

Visitors can browse upcoming events such as concerts, parties, conferences, festivals, and other experiences.

Users can search for events by name, location, category, date, and price.

Each event should have its own page with photos, descriptions, venue details, date, time, and ticket prices.

The homepage should feature popular, upcoming, and recommended events.

2. User Accounts

Users can create accounts and log in.

Users can view their purchased tickets and order history.

Users can save events they are interested in.

3. Event Organizer Dashboard

Event organizers can register and create their own event listings.

Organizers can upload images, add event details, set ticket prices, and specify the number of available tickets.

They can manage their events, view ticket sales, and see attendee information.

Organizers should have a dashboard where they can manage everything without contacting me for every change.

4. Online Ticket Sales and Payments

Visitors can purchase tickets directly through the website.

The website should support secure online payments using suitable payment providers.

Buyers should receive an email confirmation after a successful purchase.

Tickets should be generated automatically and include unique QR codes.

The system should prevent the same ticket from being used multiple times.

5. Event Check-in

Event organizers should be able to scan QR codes at the entrance.

The system should verify whether a ticket is valid and mark it as used after check-in.

Organizers should be able to view attendee lists and check-in statistics.

6. Admin Dashboard

I need a private dashboard to manage the entire platform.

I should be able to manage users, organizers, events, tickets, transactions, and reported listings.

I should be able to approve, reject, or remove events when necessary.

I need access to sales reports and platform activity.

7. Notifications

Automated emails for account registration, purchases, and ticket delivery.

Notifications to organizers when tickets are sold.

Important event updates and cancellation notifications.

8. Modern Design

A clean, premium-looking interface.

Fully responsive design for phones, tablets, and desktops.

Fast loading, easy navigation, and a smooth checkout experience.

A professional homepage, event listing pages, event details pages, and dashboards.

Additional Requirements

The platform should be designed so that additional features can be introduced as the business grows.

Security and protection of user information are important.

I want to own the website, source code, domain, and associated business data.

The website must be deployed and working on my own domain.

I need guidance on hosting, maintenance, and any ongoing costs.

What I Expect From the Freelancer

I am looking for someone who can manage the complete project, including:

Understanding my requirements and suggesting improvements.

Designing the website and user experience.

Developing the website and its functionality.

Integrating payments, email notifications, and ticket QR codes.

Testing the platform thoroughly before launch.

Deploying the finished website and showing me how to use the admin dashboard.

Please explain your proposed approach in simple language. I am open to your recommendations on the technology and tools needed.

Deliverables

A fully functional event discovery and ticket booking platform.

A customer account and ticket management system.

An event organizer dashboard.

An administrative dashboard.

Payment integration and automated ticket generation.

QR code ticket verification and event check-in.

A responsive, professional website deployed to my domain.

Source code, documentation, and basic training.

When Applying, Please Answer These Questions

Have you built an event booking, ticketing, or marketplace platform before? Please share examples.

How would you approach building this project?

What information or decisions would you need from me before starting?

How long would the project take, and what would your estimated cost be?

What ongoing hosting, maintenance, or third-party costs should I expect?

I am looking for a developer who communicates clearly, makes sensible recommendations, and can take responsibility for delivering a complete working product.

We're looking for an experienced AI full-stack developer to help resolve issues in our existing AI-powered SaaS application.

The app allows users to upload PDF documents, ask questions, and receive AI-generated answers based on their files. However, we're facing issues with inaccurate AI responses, document retrieval, occasional API failures, and slow response times.

We need someone who can review the existing codebase, identify the root causes, and fix these issues without rebuilding the entire application.

Requirements:
- Strong experience with React, Next.js, Python, or Node.js.
- Experience integrating OpenAI or other LLM APIs.
- Knowledge of RAG pipelines, embeddings, and vector databases.
- Ability to debug APIs, optimize performance, and resolve frontend/backend issues.

Please share examples of similar AI applications you've worked on and briefly explain how you'd approach troubleshooting these problems. We're looking for someone who can start with an initial assessment and then implement the necessary fixes.

# AI Specialist – Terminal-Bench & Outlier Projects

**Position:** AI Specialist / AI Evaluation Engineer
**Work Type:** Remote, Contract
**Project Focus:** Terminal-Bench, AI agent evaluation, and coding task benchmarks

## About the Role

We are looking for an experienced AI specialist with practical experience working on Outlier AI projects, particularly Terminal-Bench and terminal-based coding agent evaluations.

The ideal candidate understands how to evaluate AI agents on complex software engineering tasks in command-line environments, analyze model behavior, troubleshoot execution failures, and produce accurate, reproducible evaluation results.

This role is best suited to someone who has already worked on similar AI training, coding evaluation, or agent benchmarking projects and can demonstrate strong technical judgment.

## Responsibilities

- Perform technical evaluations of AI-generated solutions in terminal-based environments.
- Work with software development tools, command-line interfaces, Git, Linux, and automated test suites.
- Analyze AI agent performance on coding, debugging, system administration, and software engineering tasks.
- Investigate failed executions, incorrect outputs, environment configuration issues, and test failures.
- Review task instructions, expected outcomes, evaluation criteria, and test reliability.
- Produce clear, evidence-based assessments of AI-generated work.
- Maintain reproducible testing procedures and document technical findings.
- Collaborate remotely with project leads and other AI evaluation specialists.

## Required Qualifications

- Demonstrable experience with Outlier AI projects, especially Terminal-Bench or closely related coding-agent evaluation work.
- Strong command-line and terminal troubleshooting skills.
- Proficiency in Linux, Git, scripting, and software debugging.
- Experience with at least one programming language, such as Python, JavaScript, Java, or C++.
- Ability to read code, execute tests, diagnose failures, and distinguish genuine solution errors from environment issues.
- Strong analytical thinking and attention to detail.
- Excellent written English and the ability to explain technical findings clearly.
- Ability to work independently in a remote, project-based environment.

## Preferred Qualifications

- Experience evaluating AI coding agents and autonomous terminal agents.
- Familiarity with benchmark-driven evaluation, automated grading, test harnesses, and containerized environments such as Docker.
- Experience with software engineering benchmarks, reproducibility, and task verification.
- Familiarity with Python-based evaluation infrastructure and CI/CD workflows.
- Experience with other AI training or evaluation platforms.

## Application Requirements

Please include the following in your application:

1. A brief summary of your experience with Outlier AI projects.
2. Specific experience with Terminal-Bench or similar terminal-based AI evaluation benchmarks.
3. Your technical background, including programming languages and development environments.
4. Examples of relevant evaluation, debugging, or benchmark work, without disclosing confidential project information.
5. Your availability and preferred contract arrangement.

**Important:** We are prioritizing candidates with verifiable, hands-on experience rather than general familiarity with AI tools.

## How to Apply

Submit your technical background and a short description of your most relevant AI evaluation experience. Qualified candidates may be invited to complete a practical technical assessment.

Skills: Linux, Engineering, Training, Computer Security, AI Model Development, AI Automation, AI Training Data

## About Solenith Technologies

Solenith Technologies, LLC is a growing technology company focused on developing innovative, scalable, and secure cloud-based software applications.

We are seeking an experienced **Senior AWS DevOps Infrastructure Engineer with strong Terraform expertise** to review our existing AWS infrastructure, evaluate its current configuration, identify potential improvements, and provide recommendations for long-term scalability, security, automation, and cost efficiency.

Our infrastructure is already partially established. We are not looking for someone to immediately rebuild our environment. Instead, we need a knowledgeable professional who can assess what is currently in place, identify gaps, and help us develop a clear roadmap for improvement.

This is an initial short-term engagement with the potential to develop into a long-term working relationship.

## Project Overview

We are looking for a senior-level AWS professional who has extensive experience with AWS cloud architecture, Terraform Infrastructure as Code (IaC), serverless applications, CI/CD pipelines, and multi-environment infrastructure.

Our goal is to ensure that our existing AWS infrastructure follows best practices and can support multiple proprietary software applications as our company grows.

We are particularly interested in reviewing our current architecture and preparing for separate **DEV, TEST/STAGING, and PROD environments across three AWS accounts**, managed through Terraform.

The ideal candidate will independently assess our infrastructure, identify security and operational risks, recommend improvements, and communicate findings clearly.

## Current Technology Stack

Our existing and planned infrastructure includes:

**AWS Cloud Services**
- AWS Lambda (Python)
- Amazon API Gateway (REST API)
- Amazon RDS MySQL
- Amazon S3
- Amazon Cognito
- AWS Amplify Hosting
- Amazon EventBridge
- Amazon SQS
- Amazon SNS / AWS End User Messaging (SMS)
- Amazon Bedrock
- Amazon CloudWatch
- Amazon VPC
- AWS IAM
- Amazon Route 53
- AWS Certificate Manager (ACM)
- AWS Organizations

**Infrastructure & Development Tools**
- Terraform (Infrastructure as Code)
- GitHub / GitHub Actions
- React / Vite / JavaScript
- Python
- Stripe API integrations

Candidates should have strong hands-on experience with the core AWS services listed above and be comfortable evaluating how these services integrate within a secure, scalable architecture.

## Scope of Work

### 1. AWS Infrastructure Review

Review our existing AWS infrastructure and evaluate the overall architecture.

Responsibilities include:
- Assess existing AWS resources and configurations.
- Identify potential security vulnerabilities and architectural concerns.
- Review how AWS services communicate and integrate.
- Evaluate infrastructure scalability, reliability, and availability.
- Identify opportunities for cost optimization.
- Recommend improvements based on AWS best practices.

### 2. Terraform Infrastructure as Code Assessment

We want to establish a consistent Terraform-based approach for managing our AWS infrastructure.

Responsibilities include:
- Review existing Terraform configurations, if available.
- Identify AWS resources that should be managed through Terraform.
- Recommend reusable Terraform modules and directory structures.
- Review Terraform state management, remote backend configurations, and state locking.
- Recommend approaches for managing environment-specific variables and resources.
- Evaluate Terraform security and deployment practices.
- Provide recommendations for maintaining infrastructure consistency across environments.

### 3. Multi-Account AWS Environment Strategy

We are preparing to maintain three separate AWS environments:

- DEV – Development
- TEST/STAGING – Testing and validation
- PROD – Production

Responsibilities include:
- Evaluate the existing AWS account structure.
- Recommend a secure multi-account architecture using AWS Organizations.
- Review IAM roles, permissions, and account isolation.
- Recommend Terraform deployment strategies across AWS accounts.
- Identify configuration and security considerations for each environment.
- Recommend best practices for separating production and nonproduction workloads.

### 4. AWS EventBridge, SQS, and Lambda

Review our event-driven and asynchronous processing architecture.

Responsibilities include:
- Assess EventBridge rules, schedules, and Lambda integrations.
- Review SQS queue configurations and message processing.
- Evaluate retry mechanisms, dead-letter queues, and error handling.
- Identify opportunities to improve reliability and scalability.
- Recommend Terraform management for event-driven resources.

### 5. AWS Amplify and Frontend Hosting

Review the architecture supporting our React-based applications.

Responsibilities include:
- Evaluate AWS Amplify Hosting configurations.
- Review frontend deployment processes.
- Assess integration between Amplify, Cognito, and API Gateway.
- Review environment variables, custom domains, DNS, and SSL configurations.
- Recommend secure deployment practices across development, staging, and production.

### 6. SMS Messaging Infrastructure

Review our existing or proposed AWS SMS messaging architecture.

Responsibilities include:
- Evaluate Amazon SNS and AWS End User Messaging integrations.
- Review SMS notifications triggered by Lambda or EventBridge.
- Assess message delivery monitoring and error handling.
- Identify security, registration, compliance, and cost considerations.
- Recommend reliable and scalable SMS infrastructure.

### 7. CI/CD and Deployment Automation

Review our current deployment approach and recommend improvements.

Responsibilities include:
- Evaluate GitHub repositories and existing deployment workflows.
- Recommend GitHub Actions pipelines for Terraform and AWS deployments.
- Review secure AWS authentication using GitHub OIDC and IAM roles.
- Recommend automated testing, validation, and deployment approvals.
- Assess deployment processes for Lambda functions and Amplify-hosted applications.
- Identify opportunities to reduce manual deployments and configuration errors.

### 8. Security, Monitoring, and Cost Optimization

- Review IAM permissions and access controls.
- Evaluate network security and infrastructure configurations.
- Review CloudWatch logging, monitoring, and alerting.
- Assess secrets management and encryption practices.
- Identify opportunities to optimize AWS infrastructure spending.
- Recommend backup and disaster recovery improvements.
- Highlight critical infrastructure risks requiring immediate attention.

## Expected Deliverables

At the conclusion of the initial engagement, we expect the following:

**1. AWS Infrastructure Assessment Report**

A written assessment outlining the current architecture, identified concerns, potential risks, and recommended improvements.

**2. Terraform Assessment and Recommendations**

A review of existing Terraform configurations and recommendations for reusable modules, state management, environment separation, and infrastructure automation.

**3. Multi-Environment Architecture Recommendations**

A proposed approach for managing DEV, TEST/STAGING, and PROD environments across separate AWS accounts.

**4. AWS Service Integration Review**

An assessment of how Lambda, API Gateway, RDS, Cognito, Amplify, EventBridge, SQS, SMS, and other services interact.

**5. Security and Cost Optimization Recommendations**

A summary of security concerns, operational risks, and opportunities to improve efficiency and reduce unnecessary AWS spending.

**6. Prioritized Implementation Roadmap**

A clear action plan identifying:
- Critical issues requiring immediate attention.
- Recommended architectural improvements.
- Terraform and CI/CD enhancements.
- Suggested implementation priorities.
- Estimated effort for future implementation work.

**7. Final Technical Review Meeting**

A meeting with company leadership to discuss findings, answer questions, and review recommended next steps.

We expect practical, actionable recommendations rather than generic AWS documentation.

## Required Skills and Experience

- Minimum 5 years of hands-on AWS cloud infrastructure or DevOps experience; 7+ years preferred.
- Advanced experience with Terraform Infrastructure as Code.
- Experience reviewing and optimizing existing AWS environments.
- Strong knowledge of AWS Lambda, API Gateway, RDS MySQL, Cognito, S3, IAM, and VPC.
- Experience with Amazon EventBridge and SQS.
- Familiarity with AWS Amplify Hosting and React frontend deployments.
- Experience with AWS SMS messaging services.
- Knowledge of AWS Organizations and multi-account architecture.
- Experience with GitHub Actions and CI/CD automation.
- Strong understanding of AWS security, monitoring, and cost optimization.
- Ability to independently identify infrastructure issues and recommend solutions.
- Strong written and verbal communication skills.

**Preferred Qualifications**
- AWS Certified Solutions Architect.
- AWS Certified DevOps Engineer.
- HashiCorp Terraform Associate certification.
- Experience supporting SaaS applications.
- Experience with Python-based serverless architectures.
- Experience with Amazon Bedrock or AI-enabled applications.

## How We Work

We value clear communication, accountability, technical expertise, and collaboration.

Our ideal contractor is someone who can work independently while keeping our team informed of findings, potential risks, and recommendations.

We expect:
- An initial kickoff meeting to discuss our existing infrastructure and assessment objectives.
- Clear communication throughout the engagement.
- Regular progress updates through Upwork messaging or scheduled meetings.
- Documentation of identified issues and recommended solutions.
- Proactive communication when critical concerns are discovered.
- A final review meeting to discuss findings and next steps.

We prefer professionals who can explain complex technical concepts in a clear, practical manner.

**Security is important to us.** Access to AWS resources will be limited to what is necessary for the assessment. Contractors must follow our security and confidentiality requirements. No production infrastructure changes should be made without prior written authorization.

## Project Duration & Engagement

This is an initial short-term engagement focused on reviewing and assessing our existing AWS infrastructure.

We anticipate approximately **15–20 hours of work over 1–2 weeks**, depending on the complexity of the current environment.

The initial engagement will focus on infrastructure assessment, documentation, and recommendations. Implementation work will be discussed and approved separately.

We are looking for an experienced professional who can work efficiently, communicate findings clearly, and provide actionable recommendations.

Successful completion of the initial engagement may lead to ongoing opportunities involving Terraform implementation, AWS infrastructure improvements, CI/CD automation, and long-term DevOps support.

## Ideal Candidate

We are looking for a professional who:
- Has senior-level AWS infrastructure knowledge and strong Terraform skills.
- Can independently assess an existing AWS environment.
- Understands AWS security, scalability, reliability, automation, and cost management.
- Has experience supporting production SaaS applications.
- Can identify architectural weaknesses and recommend practical solutions.
- Provides clear technical documentation and actionable recommendations.
- Communicates effectively with technical and nontechnical stakeholders.
- Is interested in establishing a long-term professional relationship.

## How to Apply

Please provide the following information in your proposal:

1. A brief introduction describing your AWS DevOps and Terraform experience.
2. Examples of AWS infrastructure assessments or optimization projects you have completed.
3. Your experience managing AWS infrastructure using Terraform across multiple environments.
4. Your experience with EventBridge, SQS, Amplify, and SMS messaging infrastructure.
5. Your proposed approach to reviewing our existing AWS environment.
6. Your availability and estimated time required to complete the initial assessment.
7. Any relevant AWS or Terraform certifications.

**Please begin your proposal with "AWS Infrastructure Review" so we know you have carefully reviewed the project requirements.**

We are looking for a reliable, knowledgeable professional who can help us evaluate and strengthen our AWS infrastructure and potentially become a long-term DevOps partner.

**Solenith Technologies, LLC**

*Building Secure, Scalable, and Innovative Technology Solutions.*

We need senior engineers who can take an AI idea and turn it into something real that people use every day. You should be comfortable building with LLMs and data, and just as comfortable shipping the product around it. You'll work on AI agents, ML models, data platforms, dashboards and full applications for clients across many industries. We are hiring 5 people; each will lead in 1–2 areas and support the rest of the team.

Responsibilities
• Run AI discovery sessions and turn business problems into AI strategies, roadmaps, PoCs and production MVPs.
• Integrate LLMs (OpenAI, Claude, Gemini, Llama, Mistral) and build NLP features, RAG pipelines, AI agents, agentic workflows and agentic OS setups.
• Set up AI ops, governance and AI gateways: guardrails, evaluation, monitoring, cost and access control.
• Build machine learning solutions: computer vision, predictive analytics and intelligent process automation, deployed with MLOps.
• Design data pipelines (ETL/ELT), data warehouses and real-time analytics; modernize legacy data and enforce data governance.
• Create business intelligence reports and custom dashboards in Power BI, Tableau or Looker.
• Design and develop full-stack products and applications, integrate third-party APIs, and modernize legacy systems.
Required skills and experience
• 6+ years of professional experience in software, AI/ML or data engineering, including 2+ years with LLMs or ML in production.
• Expert Python and/or TypeScript; strong system design, clean code, testing and Git workflows.
• Proven delivery of at least 3 production projects (AI agents, ML models, data platforms or SaaS products) with links or case studies.
• Hands-on with AWS, Azure or GCP, Docker and CI/CD.
• Senior communication: able to lead client calls, estimate work and explain technical trade-offs clearly.

Tools and technologies
• AI & LLMs: OpenAI, Anthropic Claude, LangChain, LangGraph, LlamaIndex, CrewAI, MCP, Pinecone, pgvector, Weaviate, LangSmith
• ML & MLOps: PyTorch, TensorFlow, scikit-learn, OpenCV, YOLO, XGBoost, MLflow, SageMaker, Vertex AI
• Data & BI: SQL, Spark, Snowflake, Databricks, BigQuery, dbt, Airflow, Kafka, Power BI, Tableau
• Product: React, Next.js, Node.js, FastAPI, Django, PostgreSQL, REST, GraphQL, Docker

Expected deliverables
• Working PoCs, MVPs and production features with clean, tested and documented code.
• Architecture diagrams, data models, dashboards and weekly progress updates.

We are looking for an experienced Python developer to help automate repetitive tasks and improve workflow efficiency.

The ideal candidate should have experience with Python scripting, web scraping, API integrations, data processing, and browser automation using Selenium or Playwright.

Please share your relevant experience, previous automation projects, availability, and hourly rate. This could lead to long-term collaboration.

Skills: Python, Data Processing, Web Scraping, Software Development, Scripting, Data Visualization, Data Analysis, DevOps, Automation, API Integration

We run an AI detection system on live camera feeds, and we need a Django backend engineer to make the model-serving side faster, more stable, and easier to scale. The detection models already exist. The job is to make the backend that feeds them frames and handles their output run well in production.

What you’ll work on:

Profile and optimize the pipeline from live stream to model inference to results, and remove latency and throughput bottlenecks
Build a frame-handling layer in Django that manages concurrent streams without dropping or backing up frames (threading, multiprocessing, or Celery workers)
Implement frame-skipping, batching, queueing, and backpressure strategies so inference keeps up under load
Build the backend around the detection models: loading, versioning, swapping, and rollback of model versions without downtime
Store and process detection results in PostgreSQL, with careful indexing and query optimization for high-volume event data
Build the Django REST Framework endpoints for detection events, stream and camera configuration, and model status
Add monitoring and logging for latency, FPS, queue depth, and failure rates, plus automatic stream reconnect and recovery
Document the architecture and optimizations you make

Required skills:

Strong Python and Django/DRF, with production experience
Concurrency and performance tuning (threading, multiprocessing, asyncio, Celery)
PostgreSQL query optimization
Redis or a similar queue/cache
Experience profiling and debugging slow or unstable backend systems

Nice to have:

Familiarity with OpenCV and RTSP streams
Experience serving ML models (ONNX, PyTorch, Triton)
Docker and CI/CD

We’re a software development agency building web applications, SaaS products, and custom software for businesses. We’re looking for an experienced Senior Software Engineer based in the US to contribute directly to our ongoing projects.

This is a flexible, part-time role - ideal if you have a strong engineering background and prefer high-impact coding and technical work without a full-time commitment.

What You’ll Do
- Write, review, and improve production-quality code
- Design and implement system architecture and core features
- Build and maintain APIs, backend services, and database layers
- Collaborate with the team on technical implementation and code reviews
- Identify and resolve technical issues in active projects
- Contribute to technical documentation and implementation plans
- Participate in technical discussions and planning as needed

Requirements
- 8+ years of professional software engineering experience
- Master’s degree (or higher) in Computer Science or a related field
- Strong hands-on experience with web development, APIs, databases, and software architecture
- Proven track record of delivering production software
- Ability to write clean, maintainable code and clearly explain technical decisions
- Comfortable working independently and with remote teams
- Strong English communication skills
- Flexible availability for occasional meetings and focused work sessions

Nice to Have
- Experience as a Senior Engineer or Tech Lead
- Background in SaaS or custom application development
- Hands-on experience with AWS, Azure, or other cloud platforms
- Previous work with distributed teams

Schedule
- Fully remote
- Hours vary based on project needs (some weeks may require several hours of development, reviews, or discussions)
- No fixed daily schedule and no guaranteed minimum hours
- Project details and documentation will be shared in advance whenever possible

How to Apply
Please send a short introduction that covers your software engineering experience, your main areas of technical expertise, and your general availability.

We’re looking for someone experienced, reliable, and comfortable contributing high-quality engineering work on a flexible, long-term basis.

About the Company and Project

IRB Assist is an early-stage startup developing an AI-powered platform designed to streamline the Institutional Review Board (IRB) review process and support regulatory decision-making in human-subjects research.

Our platform will help IRB professionals review research protocols and informed consent documents, identify potential regulatory and ethical concerns, and improve the efficiency and consistency of the review process.

We have received an NIH Small Business Innovation Research (SBIR) Phase I award and are now building our initial working prototype.

We are looking for an experienced Full-Stack Developer to lead the implementation of the platform's core frontend and backend functionality.

Position Details

- Position: Full-Stack Developer
- Compensation:~$50 per hour
- Estimated Commitment: Approximately 400–440 hours
- Project Period: November 2026 - August 2027
- Schedule: Part-time, remote, and flexible
- Potential Growth: Opportunities for continued involvement and increased compensation if we successfully secure Phase II funding

The role is deliverable-focused, with flexibility to manage your schedule around project needs and agreed-upon milestones.

Role Overview

The Full-Stack Developer will be responsible for building and integrating the core functionality of IRB Assist's Phase I prototype.

This includes developing the user-facing application, implementing backend services and APIs, integrating document storage and database systems, and connecting AI-generated outputs to the user interface.

The goal is to build a functional, secure, reliable, and maintainable prototype that allows IRB reviewers to upload research documents, interact with AI-assisted analysis, and review findings within an intuitive application.

You will work closely with our Director of Software Engineering, UX/UI Designer, Data Architect, and AI/NLP Engineer.

You will not be expected to independently design the entire system, develop the AI models, or manage every technical component. Each team member has defined responsibilities, with collaboration across shared functionality and integration points.

Key Responsibilities

1. Frontend Development

- Develop responsive, user-friendly interfaces using React and related technologies.
- Implement dashboards, document viewers, forms, and reviewer workflows.
- Translate UX/UI designs and mockups into functional application features.
- Build interfaces that display AI-generated findings, supporting references, and reviewer feedback.
- Ensure frontend components are consistent, maintainable, and responsive.

2. Backend Development

- Develop backend functionality using Python and frameworks such as FastAPI or Django.
- Build and integrate APIs supporting the platform's core features.
- Implement user authentication, authorization, and appropriate access controls.
- Develop functionality for uploading, retrieving, and managing research documents.
- Implement backend workflows connecting application features, databases, and AI services.

3. AI/NLP Integration

- Collaborate with the AI/NLP Engineer to integrate AI-generated analysis into the application.
- Connect backend services to AI/NLP components and retrieval workflows through APIs.
- Develop interfaces for displaying regulatory findings, source references, and supporting explanations.
- Implement features that allow reviewers to evaluate findings and provide feedback.
- Support appropriate error handling and clear presentation of AI outputs.

4. Database and System Integration

- Collaborate with the Data Architect to implement database connections and data-management functionality.
- Integrate document storage, user information, research submissions, and AI findings.
- Ensure information flows reliably between frontend, backend, databases, and AI components.
- Support data integrity, appropriate security controls, and traceability.

5. Testing, Deployment, and Documentation

- Participate in code reviews, troubleshooting, and software testing.
- Collaborate with the QA Engineer to identify and resolve defects.
- Support application deployment and development environment configuration.
- Document code, integrations, and implementation decisions.
- Help ensure the prototype is secure, reliable, and maintainable.

Relevant Technical Experience

We are particularly interested in candidates with experience in:

- Python and backend application development
- React, JavaScript, and/or TypeScript
- FastAPI or Django
- Full-stack web application development
- REST API design and integration
- SQL databases, preferably PostgreSQL
- Authentication, authorization, and secure application development
- Cloud infrastructure, preferably AWS
- Git, version control, and collaborative development workflows
- Building and deploying production web applications

Additional experience with the following would be valuable:

- Integrating large language models (LLMs) into software applications
- Retrieval-augmented generation (RAG) systems
- Document processing, PDF handling, and file-management workflows
- AI-powered SaaS products
- Healthcare, clinical research, or regulated environments
- Systems requiring auditability, data security, and traceability

Prior AI/LLM experience is beneficial but not required. We have a dedicated AI/NLP Engineer responsible for the AI-specific components.

Phase I Technical Team

You will join a collaborative technical team with clearly defined responsibilities:

- Director of Software Engineering: Technical leadership, system architecture, development standards, and engineering coordination.
- Full-Stack Developer:Frontend and backend development, application functionality, and system integration.
- Data Architect: Database design, data organization, secure storage, and data architecture.
- AI/NLP Engineer: AI model integration, natural-language processing, regulatory knowledge retrieval, and AI evaluation.
- UX/UI Designer: User experience, interface design, and workflow development.
- QA Engineer: Software testing, quality assurance, and technical verification.

Each team member will have ownership of their respective area while collaborating on shared technical requirements.

We value clear communication, independent problem-solving, and practical engineering decisions. Our approach is to **build lean, but build professionally**, prioritizing functionality, security, maintainability, and thoughtful technical design.

What Success Looks Like

By the end of Phase I, we aim to have:

- A functional web-based prototype with an intuitive reviewer interface.
- Working document upload, storage, retrieval, and viewing capabilities.
- Successful integration of the platform's frontend, backend, database, and AI/NLP components.
- An interface that presents AI-generated findings and allows reviewers to assess and provide feedback.
- A secure, reliable application that supports technical verification and usability testing.
- Well-documented, maintainable code that provides a strong foundation for future development.

How to Apply

If you're interested, please share:

1. A brief overview of your relevant full-stack development experience.
2. Examples of web applications or platforms you've built.
3. Any experience integrating AI/LLM features into applications.
4. Your general availability for part-time work over the coming months.

I am looking for someone to setup Claude automations with wiza and instantly.

Some other automations in HubSpot and Claude to help automate tasks would also be helpful.

Our current goal is to consolidate the customer data and prepare four segments: Lapsed, Proposal Abandoned, Web Engagers, and Product Expiration. I'll use Python and Pandas to clean and reconcile the data, match customer accounts with contact details, preserve customer classifications, and keep suppression records separate. I'll also provide clean segment-wise exports, a summary of unmatched records, and a reusable processing script.

To proceed, I'll also need Google Analytics access for we

Work Arrangement: Remote
Engagement Type: Freelance / Contract
Timezone: EST
Duration: Project-based, with potential for ongoing work

#About the Company
We develop products and digital solutions that help shape the transportation industry, spanning cars, trains, aircraft, airports, roads, and ports. Our work supports the products, infrastructure, and technologies that keep the world moving.

#Project Overview
We are looking for a skilled Freelance Back-End Developer to develop, maintain, and improve the server-side functionality of our web applications and websites.
The ideal candidate will have experience with Haskell and PostgreSQL, building reliable back-end functionality, developing APIs, managing databases, and implementing business logic. You will collaborate with front-end developers and other team members to ensure the back-end integrates smoothly with user-facing interfaces and meets approved technical and business requirements.
The initial engagement will be project-based, with the possibility of ongoing development and maintenance work.

#Scope of Work
Develop, implement, and maintain server-side application functionality using Haskell.
Design, build, and maintain APIs for front-end and third-party integrations.
Design, manage, and optimize PostgreSQL databases, queries, and data structures.
Implement business logic, data processing, and application workflows.
Integrate back-end services with front-end interfaces and external platforms.
Implement authentication, authorization, and data-validation mechanisms as required.
Identify and resolve bugs, performance issues, and integration errors.
Optimize application performance, database queries, and code efficiency.
Maintain clean, reusable, secure, and well-documented code.
Collaborate with front-end developers to ensure smooth data exchange and functionality.
Test back-end features and validate functionality before delivery.
Maintain and improve existing systems based on approved requirements.
Document APIs and relevant technical processes.

#Required Skills
Haskell: Experience developing server-side applications using Haskell.
PostgreSQL: Experience with relational database design, SQL queries, data management, and query optimization.
Back-End Development: Strong understanding of server-side architecture, business logic, and application workflows.
API Development: Experience building and integrating REST APIs or other relevant API architectures.
Database Integration: Ability to connect back-end applications to PostgreSQL and manage data reliably.
Authentication and Security: Understanding of authentication, authorization, data validation, and web application security.
Testing and Debugging: Ability to troubleshoot issues and validate application functionality.
Version Control: Familiarity with Git and collaborative development workflows.
Documentation: Ability to provide clear technical documentation and handover notes.
Communication: Clear written and spoken English, with regular project updates.

#Preferred Skill
Docker: Familiarity with Docker for containerization and development or deployment workflows.
Working Requirements
Must be available for remote collaboration according to mutually agreed working hours in the EST timezone.
Must have a reliable internet connection and a suitable computer for development.
Must be comfortable working with an existing codebase and collaborating with front-end developers.
Must communicate progress, clarify technical requirements, and flag potential issues promptly.
Must meet mutually agreed milestones and delivery dates.
Must follow agreed coding standards, security practices, and project requirements.

#Project Deliverables
Depending on the assigned project, deliverables may include:
Completed back-end features and server-side functionality.
Functional APIs and integrations.
PostgreSQL database structures, migrations, and optimized queries, where applicable.
Authentication and access-control functionality, where required.
Tested, maintainable, and documented source code.
API documentation and technical handover notes.
Relevant configuration and deployment documentation.
Bug fixes and revisions agreed upon in the project scope.

#How to Apply
Please include the following in your proposal:
Your portfolio or links to back-end projects you have developed.
Details of your experience with Haskell and PostgreSQL.
Examples of APIs, database integrations, or complex application features you have implemented.
Your experience working with existing codebases and front-end teams.
Your experience with Docker, if applicable.
Your hourly rate or fixed-price estimate.
Your availability and preferred working hours.
Your estimated timeline for the proposed scope of work.

Shortlisted candidates may be asked to discuss their approach to a technical requirement involving Haskell, PostgreSQL, API design, and front-end integration.

We welcome applications from capable developers regardless of formal degree or educational background, provided they meet the project's technical requirements and applicable legal requirements.

Engagement Terms
The initial engagement will be freelance and project-based, with the possibility of additional work depending on project requirements, performance, communication, and delivery quality. Project scope, pricing, deadlines, deliverables, and revision expectations will be agreed upon before work begins.

Title: Senior Data Engineer – Distributed Data Pipeline & Spatial Database Architecture
Description:
We are building an in-house real estate data engine to aggregate, clean, and enrich property records at scale across the US. We need an expert Data Engineer to architect a high-throughput data ingestion pipeline and spatial database that processes public records and integrates enriched data into our CRM APIs.
Responsibilities:
Design and deploy scalable data ingestion workflows for public county assessor portals, open datasets, and GIS APIs.
Implement robust network request management, rate limiting, and session handhandling to ensure high uptime and pipeline resilience.
Architect a PostgreSQL/PostGIS and Elasticsearch infrastructure optimized for complex spatial queries, property searches, land-use filtering, and Census data integration.
Normalize and clean large-scale unstructured/semi-structured real estate datasets.
Requirements:
Proven experience building high-throughput, distributed data pipelines and web scrapers using Python (Scrapy, Playwright, or similar).
Expertise with spatial databases (PostgreSQL/PostGIS) and Elasticsearch.
Deep understanding of HTTP request handling, IP rotation strategies, user-agent management, and distributed crawler architecture.
Prior experience working with US real estate, GIS, or public record datasets.

The problem

I’m an accountant and each month I write a management summary based on financial data extracted from Xero. I have historical extracts and the corresponding written reports, which can be used as examples of the analysis, structure and tone I need.
I’d like to automate this process to reduce the time spent drafting reports, while keeping the commentary accurate, relevant and easy to review.

My preference is to start with a programmatic, rules-based approach: calculate the relevant movements and financial indicators, then generate commentary using defined logic and templates. I’m also open to including AI where it adds clear value, provided the financial calculations remain reliable and the written output can be checked against the underlying data.
Scope of work

Phase 1: Assessment and recommendation
Review a representative sample of historical Xero extracts and their accompanying management summaries, then deliver a written recommendation covering:
• Which parts of the commentary can be automated reliably, and which require additional context or accountant judgment
• The calculations, comparisons and materiality thresholds needed to identify movements worth commenting on
• How to reproduce the structure, tone and level of detail of the existing reports
• The approach you recommend: rules and templates, AI-assisted generation, or a combination, with the trade-offs explained
• How missing data, inconsistent account mappings and unusual transactions should be handled
• A practical implementation plan, including costs, ongoing maintenance and any recurring service fees
The initial solution can work from exported Xero files. Direct integration with the Xero API can be considered if it offers a clear benefit.
Phase 2: Implementation
Build the agreed solution. Depending on the approach, this will include:
• Importing and validating the monthly Xero extracts
• Calculating the financial metrics and comparisons required by the reports
• Applying agreed rules to identify material changes, trends and exceptions
• Generating an editable management summary in the agreed format
• Making it straightforward to trace figures and statements back to the source data
• Flagging points that need review or additional explanation
• Testing the output against historical reports and refining it based on my feedback
• Providing documentation and a handover so I can run the process each month and adjust the reporting rules over time
If AI is included, it should use verified calculations and supplied context, avoid inventing explanations for financial movements, and handle confidential financial information appropriately.
Success looks like: I can provide a new monthly Xero extract and generate a consistent, accurate first draft that substantially reduces writing time. The figures reconcile to the source data, the commentary highlights the important movements, and anything requiring my judgment is clearly flagged.
Required skills
• Strong Python or comparable programming skills for data processing and reporting automation
• Experience working with accounting data and a sound understanding of profit and loss, balance sheets and management reporting
• Ability to turn reporting examples into clear calculations, rules and reusable commentary templates
• Experience validating financial outputs and handling incomplete or inconsistent source data
• Judgment about maintenance burden; I’d rather have a straightforward system I can use each month than a complex one that needs constant developer support
• Clear written English and the ability to explain technical choices to an accountant
Nice to have
• Experience with Xero exports and the Xero API
• Previous work automating management accounts or financial commentary
• Experience combining deterministic financial calculations with AI-generated narrative
• Experience generating formatted Word or similar editable reports

To apply, please tell me
• How you would decide which parts of this process should use rules and templates, and where AI might help
• A comparable reporting automation you’ve built, including the inputs, outputs and how you checked accuracy
• What sample extracts and historical reports you would need to assess the project
• How you would prevent the system from producing plausible but unsupported explanations for financial movements
• Your availability, rate and indicative cost for the initial assessment

We have an existing RAG-based system that is partially working but not performing the way we need it to. Looking for an experienced AI developer who can jump into the codebase, understand what is there, and tell us what needs to change.

This is a short review task. You will look at the current pipeline - how documents are ingested, chunked, embedded, and retrieved - and give us a written assessment of the weak points plus your recommended fixes.

Good fit if you have built or debugged RAG systems in production and work with Python and LLMs regularly. Experience with vector databases and retrieval optimization is a plus.

Walk us through a RAG pipeline issue you have diagnosed before and how you resolved it.

We process 500K customer records daily from Salesforce and need to design an AI-driven data pipeline. Currently, this takes 6 hours to do manually. We need a technical design to automate it.

YOUR TASK:
Design a data pipeline for our business that includes:
- Diagram of data flow (Salesforce → processing → data warehouse)
- Tech stack recommendation with rationale
- Pseudocode for core processing logic
- List of potential challenges & solutions

DELIVERABLES:
✓ Architecture diagram (visual - can be Lucidchart, Draw.io, or image)
✓ Design document (2–3 pages)
✓ Pseudocode snippet
✓ Risk assessment & mitigation strategies

SKILLS NEEDED:
- Data pipeline design
- Data engineering experience
- Understanding of Salesforce APIs
- Python or SQL knowledge

BUDGET: $200
TIMEFRAME: 2–3 days

screening questions:
1. "Describe a data pipeline you've designed. What was the tech stack?"
2. "How would you approach deduplicating 500K records daily?"
3. "What challenges do you foresee with Salesforce-to-warehouse pipelines?"