Staff AI Enablement Engineer
Staff-level engineer responsible for building AI agents and automation, evaluating developer AI tools, and driving adoption across the engineering organization. Requires 8+ years of software engineering experience plus production experience with LLMs, agentic systems, and applied machine learning.
About the job
Responsibilities
- Serve as the engineering subject-matter expert on generative AI, agentic systems, and AI-assisted software development.
- Meet with engineering teams to identify workflow pain points and translate them into a prioritized AI-enablement backlog.
- Own the AI enablement roadmap, secure leadership buy-in, execute it, and report on impact.
- Evaluate and pilot AI coding assistants and agentic development tools; make evidence-based adoption decisions.
- Design, build, and operate specialized automation agents for engineering and operational workflows using a shared, extensible architecture.
- Measure automation impact, including time saved, quality improvements, and adoption, and iterate based on usage.
- Partner with business, data, and clinical stakeholders to modernize rules-based and heuristic systems with data-driven or ML-informed approaches.
- Define adoption frameworks and guardrails for quality, security, cost, and responsible use.
- Promote AI and automation best practices through documentation, demonstrations, brown bags, and hands-on pairing.
- Communicate AI tradeoffs, including build versus buy, cost, latency, quality, and risk, to engineers and leadership.
Requirements
- 8+ years of software engineering experience shipping production systems end-to-end.
- Hands-on experience building with large language models and agentic systems, including prompt engineering, context and tool design, evaluation, and orchestration.
- Production experience with modern AI coding assistants and agentic developer tools.
- Working knowledge of applied machine learning fundamentals, including features, evaluation, and model selection.
- Ability to drive technical adoption across an engineering organization without direct authority.
- Strong product instincts for internal tooling, including user discovery, prioritization, and iterative delivery.
- Excellent written and verbal communication skills, including presenting roadmaps, tradeoffs, and results to engineering leadership.
- Prior staff- or principal-level individual contributor experience, ideally with cross-team or platform scope.
Nice to Have
- Experience building internal AI enablement programs, developer-experience platforms, or AI governance frameworks.
- Experience in healthcare, health technology, or another regulated industry.
- Familiarity with vector search, retrieval-augmented generation, model evaluation frameworks, and observability for LLM systems.
- Experience with conversational AI or virtual assistant products.
Compensation and Benefits
- Competitive compensation.
- Medical, dental, and vision insurance effective on the first day of employment.
- 401(k) with match.
- Generous paid time off and paid holidays.
- Paid parental leave.
- Learning and professional development support.
- Remote flexibility.
Skills
Generative AI, LLMs, Agentic Systems, Prompt Engineering, Machine Learning, Ai Coding Assistants, Vector Search, Retrieval-Augmented Generation, Model Evaluation, Llm Observability, Conversational AI, Automation Agents
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