AI Developer

Position Summary:

Title: AI Developer
Duration: 12 Months – Long Term
Location: Washington, DC 20005

Hybrid Onsite: 2/3 Days onsite per week from Day1

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.

• 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.

• Spin up end-to-end prototypes using technologies like AWS Bedrock / SageMaker, FastAPI, Streamlit React, Next.js, 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.

• 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.

• 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.

1. Aiding in creation of video demos
2. Conducting live demos

• Guide pilots through acceptance, hand-off, and sustainment planning with operations teams.

• 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.

• Bachelor's degree in technology, innovation, or related field of study.
• 3+ years delivering data products or full stack applications .
• 1+ years building & deploying GenAI applications.
• Practical understanding of technologies like:

1. AWS core services using Bedrock or SageMaker for LLM hosting
2. Java, Python, FastAPI, Docker, GitHub Actions, Terraform or AWS CDK
3. React / Next.js, TypeScript, and modern vector stores
4. LangChain, LlamaIndex, LangGraph, or equivalent RAG / agent frameworks

• Demonstrated ability to compress ideation → demo → hardened pilot into< 90 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.

“Mindlance is an Equal Opportunity Employer and does not discriminate in employment on the basis of – Minority/Gender/Disability/Religion/LGBTQI/Age/Veterans.”