AI Developer

Position Summary:

Title: AI Developer
Duration: Months – Long Term
Location: Washington, DC

Hybrid Onsite: / Days onsite per week from Day

The overall purpose of position:
Support “AI pod” and analyse client needs, stand up prototypes, and convert those prototypes into secure, production-ready applications.

• Will own the end-to-end development life cycle for changing client efforts while constantly scouting, testing, and injecting emerging AI technologies into the process.
• Candidate must pair an exceptional delivery discipline with hands-on engineering agility, moving seamlessly from whiteboard to working demo and back again.

Scope of work:

Exploration & Scoping

• Rapidly synthesize client pain points into concise problem statements, success metrics, and guardrails.
• Evaluate feasibility, cost, risk, and ROI for multiple GenAI solution paths (RAG, agentic workflows, synthetic-data pipelines, etc.).
• Aid in maintaining a dynamic backlog of ideas, continuously assisting in reprioritized against business value.

Rapid Build & Iteration

• Spin up end-to-end prototypes using technologies like AWS Bedrock / SageMaker, FastAPI, Streamlit React, , or whatever framework or architecture efficiently to meet client needs
• Implement evaluation harnesses for accuracy, latency, and cost, demo tangible progress each Sprint.
• Capture stakeholder feedback live and fold it into the next sprint with minimal overhead.

Adapt & Enhance

• Refactor architecture as user requirements shift or new data sources emerge.
• Introduce cutting-edge libraries or architectures when they offer measurable uplift.
• Document decision trade-offs and lessons learned for future waves.

Hardening & Transition

• Elevate promising POCs into client-compliant pilots and integrate CI/CD pipelines.
• Produce all delivery artifacts: architecture diagrams, security traceability, runbooks, video demos.
• Alignment to client and AFS security practices.
• Creating/Updating existing relevant client documentation.
• Aiding in creation of video demos
• Conducting live demos
• Guide pilots through acceptance, hand-off, and sustainment planning with operations teams.

Emerging-Tech Tracking & Best Practices

• Track Client GenAI trends (open-source LLMs, small-context agents, memory-efficient RAG) and run spike proofs to gauge fit.
• Present briefings to the Innovation leadership (when applicable) and seed reusable patterns into our internal asset library.
• Mentor junior practitioners on prompt engineering, token-cost governance, and evaluation best practices.

Qualification and experience:

• Bachelor's degree in technology, innovation, or related field of study.
• + years delivering data products or full stack applications .
• + years building & deploying GenAI applications.
• Practical understanding of technologies like:
• AWS core services using Bedrock or SageMaker for LLM hosting
• Java, Python, FastAPI, Docker, GitHub Actions, Terraform or AWS CDK
• React / , TypeScript, and modern vector stores
• LangChain, LlamaIndex, LangGraph, or equivalent RAG / agent frameworks
• Demonstrated ability to compress ideation → demo → hardened pilot into < days
• Exceptional verbal, written, and presentation skills.
• Able to translate technical insights into executive-ready stories.
• High comfort operating in fast-paced, ambiguous environments where priorities shift rapidly.

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