Staff AI Enablement Engineer

Role overview A Staff AI Enablement Engineer is needed to define how generative AI and automation are used across an engineering organization, with a hands-on builder mandate rather than an advisory one. The role pairs direct engineering of working automations and agents with cross-team enablement, helping engineering and product teams reduce toil, adopt AI coding assistants thoughtfully, and modernize legacy rules-based systems with more data-driven approaches.

Responsibilities - Serve as the engineering organization's subject-matter expert on generative AI, agentic systems, and AI-assisted development, separating durable capability from hype - Meet with every engineering team to diagnose workflows, tooling gaps, and pain points, then translate findings into a prioritized backlog of AI-enabled solutions - Own the AI enablement roadmap end-to-end: propose, secure leadership buy-in, execute, and report on impact - Evaluate and pilot AI coding assistants and agentic developer tools, driving adoption decisions grounded in evidence and team maturity - Design, build, and operate a shared architecture for specialized automation agents that can be extended quickly and reliably - Instrument every shipped automation to measure time saved, quality gains, and adoption, then iterate based on real usage - Partner with data, product, and clinical stakeholders to modernize rules-based or heuristic systems into ML-informed approaches - Define lightweight adoption frameworks and guardrails covering quality, security, cost, and responsible use - Champion AI and automation best practices through documentation, demos, brown bags, and pairing with teams - Make build-vs-buy, cost, latency, quality, and risk tradeoffs legible to both engineers and leadership

Requirements - 8+ years in software engineering with a track record of shipping production systems end-to-end - Hands-on experience building with large language models and agentic systems - Excellent written and verbal communication, with comfort presenting roadmap, tradeoffs, and results to engineering leadership - Prior experience in a staff- or principal-level individual contributor role, ideally with cross-team or platform scope

Nice to have - Experience building internal AI enablement programs, developer-experience platforms, or lightweight AI governance frameworks - Background in healthcare, healthtech, or another regulated industry - Familiarity with vector search, retrieval-augmented generation, model evaluation frameworks, and observability for LLM-based systems - Experience with conversational AI or virtual assistant products

Benefits and work setup - Medical, dental, and vision coverage effective day one of employment - 401(k) with company match - Generous paid time off plus paid holidays and paid parental leave - Remote flexibility with meaningful mission-driven work in a large-scale mental health care context