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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # FDE AI/ Solutions Architect - **Company:** PROVECTUS INC - **Location:** United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, Amazon S3, Automation of Tests, Microsoft Azure, Cloud Engineering, Continuous Integration, Github, Python (Programming Language), Cloud Services, TypeScript, Large Language Models, Multi-Agent Systems, Apache Spark, Backend, Gitlab-ci, Kubernetes, Production Code, Machine Learning Operations, Virtual Agents, Amazon Simple Queue Service (SQS), Data Pipelines - **Published:** August 5, 2026 - **Apply:** https://careers.provectus.com/vacancy/fde-ai-solutions-architect-ai-python-data-cd168e4b/ ## About the Role Mindset * Proactive and self-directed; identify problems before they're handed to you * Comfort with ambiguity and ownership. Engagements start underspecified by design. Closing that gap is the job * B2+ English, comfortable collaborating across distributed, multicultural teams Client Engagement * You are willing to spend time understanding and doing someone else's job on the client's side before you write a line of code * Credible with senior stakeholders - you can hold a redesign conversation with a BU head and a scoping conversation with a CTO, presenting outcomes to them * You can produce a scoped, phased delivery plan with clear deliverables, dependencies, and risks - and estimate what it will cost to build and to run Technical depth * 7+ years building and running production systems. * Solid AI/ML foundations. You understand what the models do well enough to reason about failure modes * Designed and shipped to production LLM applications and agentic workflows - not demos, not POCs, not notebooks * Agentic orchestration: multi-step workflows, graph-based orchestration, tool use, state management, and recovery from partial failure * Experience with LLM APIs (Anthropic, AWS Bedrock, or OpenAI) and agent frameworks. * Experience building and optimizing RAG systems in production * Strong engineering fundamentals - dropped into an unfamiliar codebase or language, you're productive. Python and/or TypeScript proficiency; depth matters more than stack. * Experience in making and defending architectural trade-off decisions * Hands-on AWS production depth: Bedrock, Bedrock AgentCore, Lambda, ECS, S3, SQS, ECR, or similar. GCP or Azure is a plus * Cloud-native delivery: containers, ECS or Kubernetes, IaC, and CI/CD applied to AI pipelines * You evaluate. You have built or owned an eval suite for a non-deterministic system, and you can explain what you measured, how you produced ground truth, and what gated a release * Model and agent monitoring, drift detection * Cost and latency discipline: model tiering, caching, and the ability to say what a workload costs to run before it runs * Hands-on production experience with the Claude ecosystem - Claude Code, CLAUDE.md, hooks, skills files. Spec-driven development - writing the intent, constraints, and acceptance criteria before you let an agent build - is a strong plus * MCP: you can say why an agent would prefer it to a REST integration. Having authored a server is a plus, * Prior experience as a founder, CTO, or engineering leader who has chosen to return to individual contribution * Experience in one of the industries: financial services, insurance, healthcare * Consulting, professional services, or other embedded customer-facing delivery * A2A: you can explain agent-to-agent interoperability * AWS and Claude Code Certifications * CI/CD pipeline experience (GitHub Actions, GitLab CI) * Experience in an additional language (Go, TypeScript, or Rust) * Experience with Apache Spark, Apache Airflow, Kafkа ## Description * Sit with the client and the Forward Deployed Executive at the start of an engagement. Learn the function from inside, not from a requirements doc, and redesign the function from first principles. * Reach working fluency in a new domain - insurance underwriting, healthcare revenue cycle, asset flow. Build * Design and ship production GenAI systems into the customer's environment (cloud-native data, LLM-based, and agentic AI solutions). Implement and optimize RAG systems for production use cases * Build the evaluation harness before you build the feature. Define what working means, instrument it, and let the evals drive the design. * Write production code across the stack - AI, backend services, data pipelines. We choose tools to fit the customer. * Take systems to production on AWS (GCP or Azure where the customer requires it): containerised, CI/CD, automated testing, monitoring, and maintainable after we leave. Hand the system over to the client. * Start from the blueprint, and feed the blueprint. What you learn in the field becomes the baseline the next engagement starts from. * Lead architecture reviews, produce technical design documents, and contribute to standards. Mentor engineers and share knowledge across the team. Own the outcome. * Work in a pair with a FDX who carries the Business Unit's KPIs. Your work is measured against the same number. * Own the technical direction of technical proposals and scoping. Drive adoption. Change management is part of the engineering job here. * Be credible with the customer's engineers and their executives. * Shape what we commit to before we commit to it., * The chance to shape how leading enterprises across LATAM, Europe, and North America adopt AI, from strategy through first deployment * A forward-deployed model working in small, senior teams alongside Principal Architects and Forward Deployed Engineers * A growing AI delivery practice where you help build the tooling and frameworks, not just use them * Remote-friendly culture * Internal training programs with full support for Claude, AWS, and other professional certifications, conference attendance * Career growth; we actively develop our engineers * Access to the latest AI tools and premium subscriptions * Long-term B2B collaboration * Private medical insurance or a budget for your medical needs * Paid sick leave, vacation, and public holidays * Equipment and all the tech you need for comfortable, productive work ## Related Videos - [Agentic employees in world's most downloaded FinTech app](https://www.wearedevelopers.com/videos/100123-agentic-employees-in-world-s-most-downloaded-fintech-app) - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [Building a Multi-Agent Orchestration Engine That Actually Follows the Rules](https://www.wearedevelopers.com/videos/100159-building-a-multi-agent-orchestration-engine-that-actually-follows-the-rules) - [Nest.js - TypeScript in the backend can also be clean](https://www.wearedevelopers.com/videos/1033-nest-js-typescript-in-the-backend-can-also-be-clean) ## Related Articles - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [9 Claude Code Skills to Speed Up Your Workflow](https://www.wearedevelopers.com/magazine/740-9-claude-code-skills-to-speed-up-your-workflow) - [Everything a Developer Needs to Know About MCP with Neo4j](https://www.wearedevelopers.com/magazine/604-everything-a-developer-needs-to-know-about-mcp-with-neo4j) - [Never delegate the understanding](https://www.wearedevelopers.com/magazine/749-never-delegate-the-understanding)