Must have
• 8+ years of healthcare industry experience: Direct, hands-on experience in health insurance operations (underwriting, claims adjudication, utilization management, product launch) or health system clinical and operational workflows not adjacent or observational. You must understand how these environments actually work.
• Proficiency with Claude (Anthropic) as a development tool. Demonstrated use of the Claude API including prompt engineering, tool use, and agentic patterns to build real applications. Using Claude as a chat interface does not qualify. You must have built with it.
• Full-stack AI engineering capability: Ability to build and ship end-to-end AI applications independently. LLM integration, retrieval-augmented generation (RAG), agentic orchestration, REST API development, and lightweight front-end interfaces sufficient to put a working demo in front of a client.
• Demonstrated ability to prototype at speed: Proven track record of moving from a business conversation to a working AI prototype in days not sprints or quarters. You can show examples of what you built, how fast, and what problem it solved.
• Business articulation and stakeholder communication: Ability to walk into a meeting with healthcare executives and explain what you built, why it matters, what it costs, and what comes next clearly, confidently, and without jargon. This is a non-negotiable for a client-embedded role.
• Maturity to engage at the executive level: Comfortable participating in steering committees, executive briefings, and business rhythm meetings without needing hand-holding. You can hold the room, handle pushback, and demonstrate progress in terms business leaders care about.
• Ability to structure ambiguous problems: When a business leader says ‘we need to reduce risk in our underwriting process,’ you know how to break that into a scoped AI opportunity with clear inputs, outputs, and success criteria before opening a laptop.
• Quantitative fluency for ROI and impact measurement: Ability to build simple but credible business cases estimating time saved, cost reduced, or revenue protected and translate AI outputs into financial terms that resonate with finance and operations leaders.