Head of AI Engineering - NCT

Role overview This is a hands-on builder-to-leader role leading the transition of a 15-year-old case-management platform used in county-level Health and Human Services operations into an AI-first product. The position begins with a strict build-solo mandate, personally designing and shipping the first version of foundational AI capabilities, then evolves into engineering leadership as the team is scaled around proven patterns. It is US-based and remote, with eligibility requirements tied to government-adjacent public-sector compliance work.

Responsibilities - Personally design and build foundational AI capabilities such as RAG systems, code generation, LLM orchestration, and multi-agent workflows that analyze legacy code and produce production-ready services. - Refactor legacy components into scalable, cloud-native services and replace manual workflows with AI-driven automation, avoiding any temptation toward a wholesale platform rewrite. - Ship features safely using feature flags, shadow mode, and monitoring while operating within HIPAA and CJIS compliance frameworks. - Once the AI factory is proven solo, take on direct delivery accountability: managing execution, raising talent density, setting engineering rhythms, and mentoring developers into an AI-native way of working. - Act as the core technical partner to the CEO while coordinating with a broader group-level AI initiative to accelerate localized product value.

Requirements - 8+ years of hands-on software engineering with a track record of modernizing complex architectures and establishing cloud-native or DevSecOps practices. - Documented history of shipping functional AI/ML systems end-to-end to real users, including data pipelines, modeling, deployment, and monitoring. - Experience operating as a founding or first AI engineer, comfortable delivering baseline architecture independently before relying on a large team. - Strong judgment on build-versus-buy and the patience to guide a long-established Microsoft-stack platform through a phased modernization. - Proven engineering team management experience and a genuine orientation toward developing technical talent. - US-based with full eligibility for government-adjacent and public-sector compliance work.

Nice to have - Direct GovTech, public-sector, or federal case-management software experience. - Familiarity with the Microsoft AI stack, including Azure ML and Azure OpenAI integrations. - Experience coordinating with distributed or offshore engineering teams.

Benefits and work setup - Long-horizon environment focused on permanent ownership rather than short exit cycles, paired with autonomy over AI strategy, tooling, and execution. - Access to a broader peer network of operating-company leaders sharing modernization playbooks and lessons.