Optimize Freelance Projects with Amazon S3

I need help setting up and managing Amazon Ads for my new brand launching on Amazon. The work includes creating campaigns, optimizing ad performance, and providing ongoing support to improve results. I’m looking for someone who can take ownership of the account, make data-driven decisions, and help grow my brand presence on Amazon.

We are looking for an experienced Amazon PPC expert to manage and optimize our Amazon advertising campaigns.

*Responsibilities:*
- Create, manage, and optimize PPC campaigns.
- Conduct keyword research and competitor analysis.
- Optimize bids, budgets, and placements.
- Analyze search term reports and eliminate wasted ad spend.
- Improve advertising efficiency, sales, and overall profitability.
- Monitor ACoS, TACoS, and ROAS to drive sustainable growth.

*Requirements:*
- Proven experience in Amazon PPC management.
- Strong analytical and campaign optimization skills.
- Experience managing established Amazon brands.

Please share your experience, past results, and relevant case studies when applying.

## 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 a freelancer to help launch and manage Amazon ads for a new brand. The work includes setting up campaigns, optimizing ad performance, monitoring results, and making ongoing improvements to increase visibility and sales. This is a short-term project for someone who can take ownership of the ad strategy and help drive strong results for the brand launch.

I need help getting my product listed on Amazon. The work includes preparing the listing, optimizing product details, and ensuring the setup is complete and ready for launch. Please share your experience with Amazon listings and any relevant examples of similar work. I’m looking for someone who can guide the process and help make the listing effective and accurate.

We're an early-stage team collecting real-world manipulation data for robot learning. Operators record tasks with a handheld gripper: a GoPro (4K, 60 fps, built-in IMU) plus force and gripper-width sensors, each running on its own clock.

We already have a Python QC prototype: data loaders, 18 automated checks (video, force, sync, gripper, SLAM pose), an HTML report and an evaluation script. We also have a written spec for how data should be stored, checked and reviewed. What we don't have yet is the production system around it. That's this job.

Milestone 1: storage and ingest
- Cloud object storage (S3 or GCS) with three zones: raw (never modified; versioning and delete lock), derived, curated
- An offload tool for field laptops: copy SD cards, checksum every file, upload, read back and verify before the card is wiped
- A per-session manifest and a Postgres schema for sessions, files and QC results
- An event-driven queue that runs our existing checks when a session finishes uploading
- Working end to end on public UMI-style sample data

Milestone 2: review
- A simple web page where reviewers watch flagged clips and confirm or overturn the result
- A form for non-technical teammates to flag problems
- A daily summary (email or Slack) and an alert when one device keeps failing the same check

Milestone 3: after our pilot data comes in
- Calibrate thresholds against human labels and harden the checks

Data volume starts at a few TB and will grow to tens of TB. One hour of video is about 45 GB per camera.

You're likely a fit if you:
- Have personally built and run a pipeline for large video or sensor data, not only contributed to one inside a big infra team
- Know S3/GCS (lifecycle, versioning, object lock, IAM), Postgres schema design, Python, and a job queue or workflow tool (SQS, Pub/Sub, Celery, Prefect, Airflow or similar)
- Are comfortable with FFmpeg and video metadata
- Can set this up on your own, document it, and hand it over cleanly
- Write clear English and can overlap 3-4 hours a day with New York time

Nice to have: ROS bags, MCAP, HDF5 or LeRobot; GoPro GPMF; time-series alignment; Docker and Terraform.

This is engineering work. No ML research or model training.

How we'll work: shortlisted candidates get the full spec and prototype under NDA. We start with a short paid scoping task (read the spec, propose architecture, stack and an estimate for Milestone 1), then go milestone by milestone. If it goes well, there is more work after this.

Rate is open. Tell us your hourly rate and how you would estimate Milestone 1.

To apply, start your proposal with the word "manifest". Then tell us about the largest video or sensor pipeline you built yourself: data volume, stack, and one thing that broke in production and how you fixed it.

We’re a vehicle electronics installation company serving commercial fleets across the US, Canada and Australia. We install dash cams, DVRs and collision avoidance systems. We run our operations on an in-house PHP/MySQL field service platform that handles customer scheduling, technician dispatch and job sheets for tens of thousands of vehicle installs a year.

We’re looking for an experienced developer to support the platform and build it out, with a focus on API integrations and practical AI features that save our technicians and office staff time.

What you’ll work on

Support and API connectivity

Review and improve existing integrations, including our telematics API integration
Troubleshoot and fix issues in a live production environment
Build reliable, well-documented communication between our platform and external services
Improve stability, error handling and logging so problems surface before users notice them

AI and automation features

Photo checks: automatically review technician job photos (10–25 per job) to flag missing required shots and obvious install problems before a job is marked complete
Serial number scanning: read serial numbers from device labels in photos and fill them into the job sheet automatically
VIN to vehicle details: scan or read a VIN and auto-populate year, make, model and other vehicle details
Further AI opportunities: we want your input. If you see places where AI can reduce manual work, we want to hear them

Customer self-scheduling and payments

Build or integrate a customer-facing booking flow connected to our website, so customers can choose a time, book and pay online
Integrate a payment processor (e.g. Stripe or Square)
Bookings flow directly into our dispatch system with no re-entry

What we’re looking for

US Eastern Timezone hours
Strong PHP and MySQL experience, including working in an existing codebase you didn’t write
Proven API integration experience with REST APIs, webhooks and authentication
Experience adding AI to a production app (OpenAI, Anthropic Claude, Google Gemini or similar), not just demos
Experience with OCR or image analysis
Payment gateway integration experience
Comfortable deploying to and working on a live Linux server
Uses Git and writes clean, documented code another developer can pick up
Cost-aware: you think about API usage costs at scale
Clear communicator who gives realistic estimates and flags problems early

Nice to have

Experience with field service, scheduling or dispatch software
Familiarity with fleet telematics or vehicle data
Experience with Cloudflare R2 or Amazon S3

Engagement

Part-time, ongoing, with room to grow as the roadmap expands
You’ll be required to sign an IP assignment and confidentiality agreement with our company before accessing the codebase

We need an n8n workflow that publishes SEO and answer-engine (AEO) content to our static website on S3 and CloudFront. It should follow a strict content template and a content calendar, with scheduling, and rebuild or upload and invalidate the cache after each post. You would deliver the workflow, the template, the calendar setup and short documentation.

We want to replace our WordPress site with a fast, plain HTML and CSS version, with no plugins or bloat. You would rebuild the existing pages, keep the SEO basics (URLs, titles, meta tags, redirects), and deploy it to an S3 bucket with CloudFront, HTTPS and a custom domain. Using Claude Code for the rebuild is part of the plan. You would hand over the repo and a deploy guide.

Senior Data Engineer — connector build on an existing AWS ingestion framework

Engagement: Fixed price, milestone-based · Remote · EU-based or EU-working-hours strongly preferred
Duration: 4–6 weeks for the first package

Background

We are a B2B analytics company in the sports and sponsorship sector. We have just completed a data-foundation build on AWS and are now extending it with additional source connectors.

The foundation already exists and is not in scope to rebuild. It comprises: a reusable ingestion framework, a landing and standardisation layer, a canonical entity model, a dbt/PySpark transformation framework, scheduled orchestration with retries and backfill, an automated data-quality and lineage layer, CI/CD, and Redshift as the analytical warehouse of record. Raw data lands on S3 in Parquet with full history retained. Everything runs inside our own AWS environment.

The framework was built to a specific standard: onboarding an additional source should be a matter of configuration against the existing pattern, not writing a new pipeline. Your work will test that claim. If you find the framework falls short of it, saying so early is part of the job and will not count against you.

The gap to close

We need additional sources connected and their fields modelled into the curated layer. Two work packages, each independently scoped. This posting covers Package A only; Package B is described so you can see the trajectory.

Package A — licensed and public third-party sources (this engagement)

Source class Access Notes
Licensed company firmographics & funding provider REST API Export caps apply on the current tier; incremental extraction required
Licensed search & web-traffic analytics provider REST API Already connected — extension only, monthly history per entity
Licensed social-listening / audience & sentiment platform REST API Already connected — extension to a second entity type, 12-month aggregates
Licensed consumer-research / audience panel platform API or platform export New connector, highest field yield of the package
Employer-review source No usable public API Bot/collector fallback, low volume, static attributes
Public no-credential web sources (3–4) Open HTTP / public endpoints Low complexity, includes a sports-statistics source and a search-interest source

Volume and shape: approximately [A] company-level entities per run at [C] runs per month, and [B] property-level entities refreshed on a slower cadence. Roughly 60 fields at company level and 70 at property level, of which a significant share are already satisfied by existing connectors or by replication of our own platform tables — your scope is the remainder. Static attributes must not be re-pulled per run; time-series values refresh on schedule with [D] of history on first load.

Entity resolution: every external source must link to our internal entity ID. Exact matches resolve automatically; ambiguous matches queue for human confirmation, and every confirmation is recorded. No linking by file name or by free-text company name alone.

Package B — contact-level enrichment (not in this posting). Person-level data from a B2B contact database with an enrichment orchestration layer. Handled separately under a data-processing agreement; mentioned only so you understand it is deliberately excluded here.

Required stack

Non-negotiable, because it must match what exists: AWS (S3, Redshift, Secrets Manager, IAM, Lambda), Parquet, dbt for SQL transformations, tests and lineage, PySpark for heavy transforms, Python, Git with PR-based review and CI. Credentials in Secrets Manager — never in code, config or environment files committed to the repo. API-first extraction; bots only where no usable API exists.

Deliverables and acceptance criteria

Each is independently testable. We will verify all of them before final payment.

Connectors. Every in-scope source lands in the S3 raw layer on schedule through the existing ingestion framework, implemented as configuration of that framework rather than a standalone pipeline. Authentication, rate-limit handling, incremental extraction and retry behaviour all demonstrated.
History retention. Nothing is overwritten. Every record carries its source and extraction timestamp. A re-run on identical inputs produces identical outputs.
Entity resolution. One table links our internal ID to every external key, with automatic exact matching, a queue for ambiguous cases, and an audit record of every confirmation.
Curated fields. All in-scope fields queryable in Redshift at the specified grain, each traceable to its source.
Quality gate. Automated tests on keys, completeness and value ranges run on every load and block bad data from reaching the curated layer. Failures alert to a channel we nominate.
Documentation and transfer. A field-level catalogue mapping each field to source, key, refresh and owner; a runbook per connector; and a recorded walkthrough. Final acceptance requires one of our own engineers to onboard a new source unassisted using your framework configuration and playbook, and to run the pipeline for one full cycle without you. This is a gate, not a formality.
Constraints
All work runs inside our AWS environment, on our repositories, under our CI standards. No data leaves it beyond the lookups each source itself requires.
We own every artifact produced — code, schemas, pipeline definitions, configuration, documentation — with no reverse-engineering restrictions on our own property. Declare in writing any pre-existing tooling of yours used during delivery, and confirm nothing of yours is required to operate the result afterwards. No component of yours may sit in the critical path.
EU/GDPR. All processing stays in EU regions. You will sign a DPA and be listed as a sub-processor.
Out of scope and not disclosed: our scoring and valuation logic, our weighting models, our product APIs and application screens, and the commercial terms attached to any entity. You do not need them and you will not receive them.
Source subscriptions and API credits are contracted and paid by us.
How to quote — read this carefully

Quotes structured as “N weeks × a team of M” will not be compared. Give us:

Total effort in person-days, split by role and seniority
Price per connector, by complexity band
Price per modelled field beyond the connector
Your day rate per role
The milestone schedule you propose and what triggers each payment

Fixed price against milestones. We do not engage on open-ended time and materials.

We are seeking a freelancer to reconfigure and troubleshoot our AWS and AWS Connect environment. The work includes reviewing current setup, identifying issues, implementing fixes, and ensuring the system operates smoothly. You should be comfortable working independently, communicating clearly, and delivering reliable results within the agreed timeline. Experience with AWS infrastructure and contact center support is important for this role.

We need an n8n workflow that publishes SEO and answer-engine (AEO) content to our static website on S3 and CloudFront. It should follow a strict content template and a content calendar, with scheduling, and rebuild or upload and invalidate the cache after each post. You would deliver the workflow, the template, the calendar setup and short documentation.

We want to replace our WordPress site with a fast, plain HTML and CSS version, with no plugins or bloat. You would rebuild the existing pages, keep the SEO basics (URLs, titles, meta tags, redirects), and deploy it to an S3 bucket with CloudFront, HTTPS and a custom domain. Using Claude Code for the rebuild is part of the plan. You would hand over the repo and a deploy guide.

I have invitation to Amazon online test. Plus if successful, looks like will have multiple interviews with real time coding.

Senior Software Engineer position.
Any help/advice is appreciated. Thank you.

AWS architect: secure hosting + CI/CD in ca-central-1 for an existing FastAPI / React / PostgreSQL app

Our project: HR / staffing web platform (FastAPI backend, React frontend, PostgreSQL 15). The code is complete and lives in a private GitHub repository. It is already prepared for AWS: environment-variable configuration, Alembic migrations, S3 storage mode, external scheduler mode, a Dockerfile, and a written porting guide (docs/PORTAGE_AWS.md) listing every variable and requirement.

The application will hold personal information of real workers (names, phone numbers, ID documents). Quebec's privacy law (Law 25) applies: all data must stay in Canada (ca-central-1), and security mistakes are not acceptable.

What I need (in MY AWS account)
1. Architecture proposal: short document, diagram, estimated monthly cost.
2. Infrastructure as code (Terraform or AWS CDK), stored in a separate private repository that I own:
- private networking; database not reachable from the internet;
- RDS PostgreSQL 15 with automated backups and the logging parameters listed in the guide;
- private S3 bucket: KMS encryption, Block Public Access, versioning with old versions expiring after 1 day, no Object Lock, lifecycle rules for backups;
- container hosting (ECS Fargate or equivalent) behind a load balancer, HTTPS with ACM, my domain;
- Secrets Manager for all secrets;
- EventBridge Scheduler (America/Toronto time zone) calling the app's /api/cron routes;
- CloudWatch logs and basic alarms; AWS Budgets cost alerts.
3. Two environments: staging and production, both empty at start.
4. Pipeline: every push to main deploys automatically to staging; production deploys only after my manual approval.
5. Handover: a written runbook (deploy, roll back, restore a backup, rotate a secret, add a user), and a successful backup-restore test.

Rules
- You do NOT modify the application code. If a change is needed (Dockerfile, health check, settings), you tell me and my developer makes it.
- You work in my account with your own IAM user or IAM Identity Center access with MFA, never with the root account. Access is removed at the end.
- You sign a confidentiality agreement. You never copy data out of the account.
- Data never leaves ca-central-1.

Acceptance criteria
- The application runs on staging, and its full automated test suite passes there.
- A backup restore into a temporary database works.
- No public S3 bucket, no public database, no wildcard IAM permissions (you show me the evidence).
- The infrastructure can be recreated from your code.

Payment: fixed price, by milestones (1 architecture, 2 infrastructure, 3 pipeline, 4 production + handover).

We’re seeking an AWS Certified Solutions Architect Trainer based in Tunisia to deliver on-site training for our B2B client. You’ll prepare and lead hands-on AWS sessions, covering core services, cloud architecture best practices, and certification exam preparation. The ideal freelancer holds an AWS Solutions Architect certification and has experience training corporate teams.

I need help connecting my Shopify store to Amazon Seller so I can sell products on Amazon. The work should include setting up the connection, ensuring product data syncs correctly, and helping me launch the integration smoothly. I’m looking for someone who can complete this entire project and troubleshoot any issues, and make sure the setup is reliable for ongoing use.

We are an established retail business with a physical store and e-commerce website. We are looking for an experienced Amazon specialist to set up our Amazon marketplace and configure everything required to start selling our products.

Our initial target market is Australia, with plans to expand into the United States once the business is established and running smoothly.

We will manage our own inventory, packing and shipping, so we require a seller-fulfilled setup rather than Fulfilment by Amazon (FBA).

The scope of work includes setting up our Amazon Seller Central account and branded storefront, configuring shipping, inventory, returns and order settings, creating reusable listing templates and bulk-upload spreadsheets if possible, integrating our existing systems where practical, and providing training so our team can manage the store independently.

We are BlenEarth Global Pte. Ltd., a Singapore-based technology company developing BlenAI, a proprietary AI intelligence platform for our global SaaS ecosystem.

We are seeking an experienced Senior Python AI Backend Developer to build the first phase of BlenAI as an independent, secure, API-first platform.

Project Budget: USD 3,000 (Fixed Price)
Timeline: 30–45 Days
Project Type: Backend Development Only

Project Requirements

1. BlenAI Core Platform

* Python and FastAPI backend.
* Integration with OpenAI and other LLM providers.
* Modular AI engine architecture.
* PostgreSQL database.
* Secure REST APIs with authentication.
* Multi-tenant architecture.
* Configurable prompts, business rules, and knowledge bases.
* Structured JSON responses.
* API usage tracking and logging.

2. AI Conversation Intelligence

* Upload and process recorded conversations.
* Multilingual speech-to-text transcription.
* Conversation summarization.
* Customer intent identification.
* Buyer requirements and budget extraction.
* Objection and buying-signal detection.
* Lead scoring.
* Automated follow-up recommendations.
* Structured conversation analysis through APIs.

3. Knowledge and Intelligence Engine

* Configurable industry-specific knowledge.
* Business rules and prompt management.
* Knowledge retrieval capabilities.
* Support for future AI model integrations.
* Extensible architecture for additional AI intelligence modules.

4. AWS Hosting and Deployment

* Docker containerization.
* AWS deployment.
* PostgreSQL database integration.
* Amazon S3 for audio storage.
* HTTPS and secure API access.
* API documentation using Swagger/OpenAPI.
* Automated testing and deployment documentation.

Important Requirements

* No frontend or mobile application development is required.
* The platform must operate independently of our existing SaaS applications.
* External applications will access BlenAI through secure APIs.
* All custom-developed source code and intellectual property must belong to BlenEarth Global Pte. Ltd. under the agreed contract.
* Development must take place in our private GitHub repository.
* AWS infrastructure and AI provider accounts will remain under our company’s control.
* The developer must agree to confidentiality and IP assignment requirements.

Required Experience

* Strong Python and FastAPI experience.
* OpenAI API and LLM application development.
* PostgreSQL and REST API architecture.
* AWS deployment and Docker.
* AI agents, structured outputs, and prompt engineering.
* API security and multi-tenant SaaS systems.
* Experience with speech transcription and conversation intelligence is preferred.

Deliverables

1. Complete BlenAI Core backend.
2. Working AI Conversation Intelligence engine.
3. Configurable knowledge and business rules.
4. Secure REST APIs.
5. AWS deployment.
6. API documentation and automated tests.
7. Complete source code and technical handover.

Future Opportunities

This is Phase 1 of a larger AI platform. We plan to develop additional intelligence engines for sales, construction, procurement, inventory, financial forecasting, and business analytics.

We are looking for a reliable developer interested in a long-term working relationship.

To Apply

Please share:

1. Examples of similar AI backend projects.
2. Your experience integrating LLMs and speech-to-text models.
3. Your proposed technical architecture.
4. Your estimated completion timeline.
5. Confirmation that you can work on a USD 3,000 fixed-price contract.

We prefer experienced AI backend engineers who have built production systems, not developers specializing only in basic chatbots.

Need a reliable go-to person to help with various Amazon-related projects. We currently have 5 tasks that need completion. The details are outlined in the attached PDF. The right freelancer should be able to manage multiple tasks, communicate clearly, and help move each project forward efficiently. If you have experience supporting Amazon initiatives and can handle a variety of related responsibilities, we’d like to hear from you.

When responding, please include a cost and timeline for this first project.

Thank you,
Herb

I need an experienced AWS and Terraform engineer for a single, well-defined task. You will follow a written runbook to deploy a cloud environment from a Terraform repository into a clean AWS account, verify that it matches the expected result, and document any deviations.

What the work involves:

Follow a step-by-step written runbook provided by us
Apply Terraform code from a private GitHub repository into a clean AWS account we provide
After deployment, run a second terraform plan to confirm no further changes are needed
Record the result of each step and note anything the runbook did not cover
No contact with the original developers during the task — this is an independent verification

What you need:

Solid AWS experience (IAM, networking, RDS, S3, compute)
Terraform experience — you must be able to follow a Terraform runbook and interpret its output
Attention to detail and clear written English for the deviation report
Available to start within the next 2–3 days

What you don’t need:

To write any code — this is execution and verification only

Deliverable: A short written record confirming the result of each step and listing any deviations from the runbook, in the format we provide.

Budget: $300 fixed price. Scope is one working day.

I need help setting up my Amazon Seller Central account to start selling in the US. The work includes creating and organizing the store, listing products, and preparing the account for a smooth launch. I’m looking for someone who can guide me through the setup process, help with account configuration, and ensure everything is ready for sales. Experience with Amazon Seller Central and US marketplace setup is important.

I am an Amazon Influencer with an established storefront and over 600 onsite product videos. I am already earning commissions, but I need help improving storefront organization, categorization, and overall strategy to maximize earning potential. I’m looking for someone who can analyze and categorize existing videos, performance data, and commission opportunities, identify missed visibility and growth opportunities, and develop a clear growth plan. This role should include hands-on guidance, actionable recommendations, and support for building a sustainable strategy that leverages my current assets and explores relevant traffic sources.

Amazon Listing & Search Visibility Forensic Specialist Needed — 3 Established ASINs

We are an established consumer products brand seeking an experienced Amazon specialist to investigate a significant and unexplained deterioration in search visibility affecting three of our established, historically successful ASINs.

These products have historically ranked at or near the top of page one in Amazon search results, both organically and through sponsored advertising, for several of our most important search terms.

Beginning in mid-2026, these products experienced dramatic declines in visibility, falling from prominent page-one positions to approximately the bottom of page two, with no meaningful recovery.

Despite countless Seller Central support tickets and live chat sessions attempting to identify and resolve the issue, we have made virtually no progress. Amazon Support has confirmed that the listings are active, buyable, and indexed, but has not provided a satisfactory explanation for the substantial loss of visibility.

After exhausting these support channels, we have decided to seek outside expertise to independently investigate what has happened to these ASINs.

An Additional Concern: Amazon's Pricing Designations

All three products have also been flagged by Amazon with a "High Price" designation, and their current selling prices exceed the "Competitive Price" benchmarks Amazon has assigned to them.

Despite repeated efforts to obtain clarification, we have been unable to determine how Amazon calculated these competitive prices or what specific data sources are being used.

Importantly, we have found no evidence that these products are being offered elsewhere at lower prices that would explain Amazon's current competitive-price assessments.

We do not know whether these pricing designations are contributing to the loss of organic or sponsored visibility, are unrelated to it, or are simply another symptom of a broader issue.

We would like the specialist to investigate these pricing assessments as part of the overall forensic review, including whether they may be affecting search visibility, advertising eligibility, or product competitiveness.

What We're Looking For

We need someone with advanced knowledge of Amazon's search ecosystem who can conduct a thorough forensic investigation into potential causes, including:

Organic search ranking and indexing issues

Sponsored advertising visibility and placement eligibility

Catalog, listing, or ASIN-level technical issues

Amazon's "High Price" designations and competitive-price calculations

Pricing competitiveness and potential visibility restrictions

Advertising campaign configuration and historical changes

Other Amazon platform factors that could explain a sudden and sustained loss of visibility

Historical Data & Tools Available

We have an active Helium 10 account with access to extensive historical performance data, including organic and sponsored keyword rankings, advertising impressions, campaign performance, and historical trends. We can provide all of the evidence that we have already presented to Amazon, as well as access to their chat responses.

We also have access to our Amazon Seller Central and Advertising Console historical data, including campaign change history, pricing history, sales performance, and other relevant account-level information.

We can provide historical performance information covering periods before, during, and after the visibility declines, allowing the specialist to investigate when the changes occurred and evaluate potential contributing factors.

We are not starting from scratch. We have substantial historical evidence available and are looking for someone with the technical expertise to analyze it, identify potential underlying issues, and determine appropriate next steps.

Our Objective

We want to understand what happened, why it happened, and what can be done to correct it.

We are not looking for routine listing optimization, keyword research, or ongoing PPC management. We are specifically seeking an experienced Amazon specialist who has successfully investigated and diagnosed unusual search visibility or ranking problems involving established ASINs.

Ideally, the engagement will result in a documented assessment of the most likely causes, supporting evidence, and recommended corrective actions.

Before Applying

Please describe any previous experience investigating Amazon listings that suddenly lost organic search rankings, sponsored advertising visibility, or both.

We would particularly appreciate examples of similar situations where you identified the underlying problem and helped resolve it.

Please also indicate your experience with:

Helium 10 historical keyword ranking analysis and Amazon advertising diagnostics

Investigating Amazon "High Price" designations and competitive-price discrepancies

Identifying potential Amazon-imposed visibility or advertising eligibility restrictions

This is a project-based consulting engagement, not an ongoing account management position.

Need someone available for a one-hour session to help me set up AWS through a screen share. I’m looking for clear guidance and hands-on support to get the setup completed efficiently. Please be comfortable explaining steps as we work through the process together.

Job Description: Data Platform Production Support Engineer (Databricks, DBT, Snowflake, SQL, Python, Spark, AWS S3, Aurora/MySQL, CDC)
Work Location: 100% Remote
Role Type: Offshore Production Support / On-Call Incident Response
Engagement Model: Part-Time, Shared Support
Work Schedule: Monday–Friday, 4:00 AM–2:00 PM Eastern Time
Technologies: Databricks, DBT, Snowflake, SQL, Python, Spark, AWS S3, Aurora/MySQL, CDC

Role Overview
We are seeking a Data Platform Production Support Engineer with hands-on experience supporting modern data platforms. The ideal candidate will troubleshoot production data pipelines, monitor workflows, investigate failures, recover jobs, execute backfills, and implement minor operational fixes through established CI/CD processes.

This is a shared, part-time production support engagement, not a dedicated full-time position. The engineer will work with the offshore delivery team and coordinate with the onshore lead to ensure timely incident handling, service continuity, and effective knowledge transfer.

Key Responsibilities
Monitor production data pipelines, Databricks Workflows, and PagerDuty alerts.
Investigate and troubleshoot failures across Databricks, dbt, Snowflake, and SQL-based data pipelines.
Perform job recovery, reruns, and backfills to restore normal operations.
Diagnose pipeline failures using Python and Spark where required.
Implement minor operational fixes through existing GitHub, CircleCI, and Databricks Asset Bundles workflows.
Support data pipelines involving AWS S3, Aurora/MySQL, and Change Data Capture (CDC).
Manage incidents from initial investigation through service restoration or a clear handoff to the appropriate engineering team.
Escalate production pipeline issues if a solution is not identified within 15 minutes.
Maintain incident tickets, operational documentation, and runbooks.
Complete end-of-window handoffs with the onshore lead, communicating incident status, outstanding issues, and required follow-up actions.

Required Skills and Experience
Hands-on experience troubleshooting Databricks Workflows, dbt, and Snowflake.
Strong SQL skills for data pipeline troubleshooting and diagnosis.
Working knowledge of Python and Spark for investigating data-processing failures.
Working knowledge of AWS S3, Aurora/MySQL, and CDC-based data pipelines.
Familiarity with GitHub, CircleCI, and Databricks Asset Bundles.
Experience monitoring production workloads, investigating incidents, recovering failed jobs, and executing backfills.
Understanding of production support practices, incident escalation, ticket management, and runbook maintenance.
Ability to work independently, prioritize incidents, and communicate effectively with distributed engineering teams.

Support Schedule and Coverage
Coverage: Monday–Friday, 4:00 AM–2:00 PM Eastern Time.
Coverage model: Shared support availability across the delivery team.
Handoff: End-of-window handoff to the onshore lead.
Monthly operations capacity: 20-30 hours

I need an Amazon expert to create and optimize product listings, manage advertising campaigns, and oversee my Amazon account. The right freelancer should be able to improve listing performance, monitor account health, and help increase visibility and sales. Experience with Amazon operations and a strong understanding of how to grow an Amazon presence are important. Please share relevant experience and examples of past work.

Abartys Health, an AWS Advanced Tier Services Partner based in San Juan, Puerto Rico, builds data, analytics, and generative AI platforms on AWS for health plans, laboratories, hospital systems, and nonprofits across the Americas. We are seeking a mid-level engineer to support client projects by building serverless backends, generative AI features on Amazon Bedrock, PostgreSQL data models on Aurora Serverless v2, and React front ends on AWS Amplify. You will also take over existing AWS builds, document them, and harden them before extending them. Projects are fixed-scope, 8 to 12 weeks, led by a senior architect, with human review built into every AI workflow. You will document your work and hand it over to client teams.

Hi, I’m looking for an experienced developer to help me build a long-term autonomous AI project, inspired by https://pinos.world/.

The vision is to create an autonomous AI character with its own personality, persistent memory, interests, goals and ongoing activities. I want something much more advanced than a standard chatbot. The character should be able to operate independently in the background 24/7, make its own decisions, pursue projects, learn from experiences and interact with the real world through controlled tools.

Core vision and functionality:

1. Autonomous AI character

- A consistent personality, preferences, interests and evolving goals.
- The ability to decide what to explore, learn about or work on without needing constant instructions from me.
- An ongoing background decision-making loop where it plans activities, takes action, evaluates results and decides what to do next.
- The ability to develop projects over time rather than simply completing isolated prompts.

2. Persistent memory and diary

- Long-term memory of conversations, experiences, decisions and previous activities.
- An automatically updated diary showing what it has been doing, discovering, creating and learning.
- The ability to reflect on previous outcomes, learn from mistakes and use relevant memories to inform future decisions.
- A transparent activity history showing what it actually did and the results of its actions.

3. Independent learning and real-world capabilities

I want the AI to be able to explore different interests and develop new capabilities over time. For example, it could decide to:

- Learn digital art, generate original artwork and build its own portfolio.
- Research ways to sell its artwork online and eventually create product listings and sell to real customers.
- Study forex markets, develop trading strategies, backtest them and learn through simulated trading.
- Learn coding, research business ideas, study science or explore any other subjects it becomes interested in.
- Use external tools, websites and APIs to carry out meaningful tasks and work towards longer-term goals.

These are examples rather than fixed instructions. The key objective is for the AI to have the freedom to choose and pursue its own projects within defined permissions and safety boundaries.

4. Direct communication

- A web-based chat interface where I can speak directly to the character.
- The ability for the character to initiate conversations and message me when it has something interesting to share, completes a task or requires my input.
- Phone notifications, ideally through a push notification system or an integration such as Telegram.
- The ability to maintain continuity between conversations.

5. Personal control dashboard

I would eventually like a dashboard where I can observe and manage the character's digital world, including:

- Its current activities, plans, goals and projects.
- Its diary, memories, progress and previous decisions.
- The ability to communicate with it directly.
- Controls to pause or resume its autonomous operation.
- Permissions for tools, websites, accounts and external actions.
- Monitoring of API usage, hosting costs and any future financial activity.
- Approval controls for sensitive actions, purchases, publishing content or handling money.

6. Progressive development

I understand this is a substantial project and that it should be developed in stages. I do not expect every feature to be available immediately.

I would like to establish a solid foundation first: the character engine, persistent memory, genuine background autonomy, diary, chat interface and a basic control dashboard.

The architecture should then allow us to expand gradually into web research, artwork generation, coding, external tool execution, online selling, simulated trading and eventually a more visual environment similar to Pino's World, potentially with an interactive 2D or 3D world and additional AI characters.

Security and reliability are important. The AI should have meaningful autonomy within boundaries I control, with appropriate safeguards around financial transactions, account access and irreversible actions.

Before proceeding, I would appreciate your thoughts on the following:

1. Is this technically achievable, and how would you approach building it?
2. What architecture, LLM and technologies would you recommend?
3. How would you implement genuine autonomy, long-term memory, goal-setting and background activity rather than simply generating scheduled diary entries?
4. Have you built similar autonomous agents or multi-agent systems before? If so, could you share examples, demos or relevant work?
5. What would you recommend including in the first development milestone, and what would be realistic to achieve at that stage?
6. What would your rough price estimate be for the initial working version, and what would you estimate for the ongoing hosting and AI API costs?
7. How would you structure the project so additional capabilities can be added over time without having to rebuild the core system?

I would also require ownership of the source code and project deliverables, along with access to the hosting environment, database and relevant documentation.

I am looking for a developer who understands both the technical requirements and the long-term vision, and who can help build this properly through a series of practical, testable milestones.

Please give me your honest assessment, recommended approach and rough costs before proposing a detailed development plan.

Thank you. I look forward to hearing your thoughts.

We are looking for an experienced Pano2VR Pro Expert / GIS Data Processor based in India for a large-scale, long-term 360° Street View mapping project spanning over 2,000 Kilometers across 2 cities.
The data will be captured via vehicle-mounted 8K 360-degree cameras and will be delivered to you in patches of 50 km.
Your Core Responsibilities:
1. Import 8K panoramas into Pano2VR Pro.
2. Perform Automatic Sequential Linking based on embedded GPS telemetry/metadata to create continuous street view navigation (similar to Google Street View).
3. Ensure no navigation arrows are broken or misaligned along the route.
4. Export the final structured CSV/Excel Image Index (containing Filename, Latitude, Longitude, Date, and Timestamp).
5. Generate Route Coverage GIS layers (KML/GPX tracks) from the project data.
6. Apply patches/blurring to public faces and private vehicle license plates for privacy compliance.
7. Deliver the output in standard HTML5 formats ready for cloud hosting (Amazon S3 / Google Cloud).
Requirements:
• Must have prior experience working with Pano2VR 7 Pro or Pano2VR 8 Pro.
• Must understand GPS metadata, Exif data integration, and auto-linking workflows.
• Must have a high-configuration workstation capable of processing thousands of 8K images smoothly.
• Communication language must be Hindi or fluent English.
Project Type: Long-term contract (Paid milestone-wise per 50 km patch delivered successfully).

Skills: Data Processing, 3D Rendering, HTML5, GPS, 3D Modelling, 3D Animation, 3D Design, 360-degree video, 3D Visualization, 3D Graphic Design

Engagement
20-week non-production build on the customer's AWS landing zone. Start expected in the coming weeks;
exact date to be confirmed. Allocation, rates, contracting terms and travel arrangements are to be agreed.
Role purpose
Deliver the machine-learning component of Aperam's Order Tolerance Management solution alongside AWS
Professional Services. Build and validate tabular classification models that recommend ways to resolve order-tolerance
problems, with clear explanations for business users.
Responsibilities
• Prepare, clean and validate model input data on Amazon S3.
• Develop tabular classification models using XGBoost and/or LightGBM; implement validation, probability calibration
and SHAP explainability.
• Implement workflows using SageMaker Processing, Training, Pipelines, Model Registry, Batch Transform and
Clarify.
• Integrate Amazon Bedrock to produce plain-language explanations of recommendations.
• Collaborate with the application engineer on prediction outputs and application integration.
• Contribute reproducible code and documentation using the agreed infrastructure and CI/CD tooling. Keep MLOps
proportionate to Phase 1, where it is explicitly light.
Required experience
• Proven personal ownership of tabular ML delivery on Amazon SageMaker, supported by project-level examples.
• Strong Python skills and experience preparing data on S3.
• Hands-on XGBoost/LightGBM modelling, model validation, calibration and explainability.
• Practical experience with the SageMaker services listed above, including batch inference and model registration.
• Ability to explain personal contribution, data/model scale and measured outcomes clearly.
Technology environment
AWS and Python; SageMaker; S3; Bedrock; Terraform; Azure DevOps CI/CD; Docker/ECR. The wider engagement
also uses Entra ID.
What to include with your application
Include project examples naming the SageMaker services used, your own implementation responsibilities, dataset
scale, validation approach, calibration and explainability work, and measured outcomes. General AWS,
data-engineering or GenAI experience alone does not establish the core requirement.
Expected outputs
Recommended delivery outputs, subject to agreement: reproducible preparation/training and batch-inference
workflows; registered model versions; evaluation and calibration evidence; explainability outputs; integration
documentation and handover.
Scope and status
Based on the AWS delivery technical lead's written requirements of 23 October 2026. Seniority and the
expected-output wording are Cloudworkz recruiting recommendations, subject to confirmation. This brief is not a
contract or an offer of employment