AI Innovation Engineer

Steampunk • McLean, VA

102d

About The Position

We are seeking a hands-on, creative, and technically strong AI Innovation Engineer to support our client delivery teams in bringing modern AI solutions to life within public-sector organizations. This role is focused on client enablement, prototyping, and cross-functional engagement—helping our clients understand the potential of AI, design proofs-of-concept, and build working prototypes that demonstrate value in their specific mission context. The ideal candidate combines strong technical skills (especially with GenAI, LLMs, data pipelines, and cloud-native services) with the ability to collaborate across disciplines—working with DevSecOps teams, cloud working groups, data stewards, and communities of practice to drive AI adoption and build momentum. You’ll play a critical role in bridging the gap between strategy and execution, demonstrating how AI can solve real-world problems and catalyze digital transformation.

Requirements

• 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.
• Familiarity 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).

Nice To Haves

• 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.

Responsibilities

• Serve as a trusted advisor to the client organization on modern AI capabilities, best practices, and responsible use.
• Develop AI education materials, tutorials, demo videos, and onboarding sessions that are tailored to the client organization’s needs.
• Lead or support AI enablement events such as workshops, lunch-and-learns, innovation sprints, and capability briefings.
• Design and implement AI prototypes and proof-of-concept solutions tailored to specific mission use cases (e.g., summarization, entity extraction, classification, semantic search).
• Work with cloud platform teams to integrate prototypes into modern cloud environments (e.g., AWS Bedrock, GCP Vertex AI, Azure OpenAI).
• Leverage RAG pipelines, orchestration frameworks (LangChain, LlamaIndex), and LLM APIs to rapidly deliver working demos.
• Participate in communities of practice and cross-team working groups (e.g., cloud, data, architecture, cybersecurity) to ensure AI adoption is aligned with broader modernization goals.
• Share findings, prototype patterns, and reusable components across delivery teams to accelerate reuse and scale impact.
• Serve as a liaison between data scientists, platform engineers, and user-facing teams to ensure end-to-end viability of AI solutions.
• Ensure all AI solutions are designed with responsible AI principles, data sensitivity awareness, and security-first practices.
• Collaborate with compliance and governance stakeholders to vet tools, define usage boundaries, and mitigate risks in AI application.

What This Job Offers