AI Innovation Engineer
On-siteMcLean, Virginia, United States
Job Summary
Serve as a trusted advisor to client organizations on modern AI capabilities, best practices, and responsible use. Develop education materials, tutorials, demo videos, and onboarding sessions tailored to specific mission needs. Design and implement AI prototypes and proof-of-concept solutions for use cases like summarization, entity extraction, and semantic search, integrating them into cloud environments using AWS Bedrock, GCP Vertex AI, or Azure OpenAI. Lead workshops, innovation sprints, and capability briefings to drive adoption. Collaborate with DevSecOps teams, data stewards, and communities of practice to ensure alignment with broader modernization goals. Share reusable components across delivery teams and act as a liaison between data scientists, platform engineers, and user-facing teams. Ensure all solutions adhere to responsible AI principles, data sensitivity awareness, and security-first practices while collaborating with compliance stakeholders to mitigate risks.
Required Qualifications
- Ability to hold a position of public trust with the US government
- Bachelor's or Master's in Computer Science, Artificial Intelligence, Machine Learning, or a related field
- 3+ years of experience in software engineering, data engineering, or applied AI/ML roles
- Demonstrated hands-on experience with modern GenAI tooling, such as: OpenAI (GPT-4), Claude, Gemini, Llama 3
- Experience with LangChain, LlamaIndex, or similar RAG frameworks
- Experience with AWS Bedrock, GCP Vertex AI, Azure OpenAI Service
- Experience with Vector databases (e.g., FAISS, Pinecone, Weaviate, Chroma)
- Strong Python development skills with familiarity in building data pipelines, API wrappers, and lightweight front-ends for demos
- Ability to build and present AI-powered demos to both technical and non-technical audiences
- Familiarity with DevSecOps and CI/CD principles
- Familiarity with GitHub
- Experience engaging with external clients or business stakeholders in a consultative role
- Relevant Professional Certification(s)
- Experience supporting HHS or NIH programs
- Experience working in scientific environments
Desired Qualifications
- Experience delivering AI capabilities into federal government agencies or highly regulated industries
- Experience customizing AI services for biomedical or health research
- Understanding of NIST AI Risk Management Framework and other public-sector digital policy memos
- Hands-on knowledge of data governance, PII handling, and compliance-aware prototyping
- Exposure to Human-Centered Design practices, user research synthesis, or journey mapping
- Prior involvement in standing up or contributing to an AI Community of Practice or Innovation Hub
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