AI Innovation Engineer
$120,000 to $180,000
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Posted 2 days ago
SENIORITY
Lead
SALARY
$120,000 to $180,000
About the role
- Client AI Enablement & Education
- 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
- Prototyping & Proof-of-Concepts
- 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
- Cross-Functional Integration
- 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
- Standards, Security & Compliance
- 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
- OpenAI (GPT-4), Claude, Gemini, Llama 3LangChain, LlamaIndex, or similar RAG frameworksAWS Bedrock, GCP Vertex AI, Azure OpenAI Service
- 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
- PreferredExperience 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.
Before you apply
Applying takes about a minute. These four things decide how fast it moves after that.
Your profile is current
It's what we read first. Occupations, seniority and locations matter more than a long history.
Two examples you can talk through
Not a portfolio — just two pieces of work where you can explain the decisions and what you'd change.
A number in mind
What you're on now and what would make you move. We negotiate better when we know both.
Your notice period
Employers plan around it, and it's the question that stalls offers most often.
Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.
