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.
Strong Preference
• Experience with agentic AI frameworks: Hands-on use of LangChain, LangGraph, CrewAI, AutoGen, or equivalent orchestration frameworks to build multi-step, tool-calling AI agents that operate in real workflows.
• Healthcare data standards and regulatory context : Working familiarity with HL7, FHIR, ICD-10, CPT, and claims data structures. Understanding HIPAA requirements, CMS regulations, and FDA digital health guidance as they apply to AI system design and deployment.
• Prior forward-deployed, embedded, or startup engineering experience: You have worked directly inside a client organization, operated in a consulting or embedded delivery model, or built products in a startup environment where you owned the full stack with limited support.
• Experience shipping AI in health insurance technology company or health system: You have navigated the additional complexity of deploying AI where compliance, audit trails, explainability, and data governance are not optional and you know how to move fast without cutting corners that matter.
• Experience contributing to reusable AI platforms or accelerators: You have built solutions with an eye toward reuse creating components, patterns, or frameworks that others on a team can adopt rather than rebuilding from scratch on every engagement.
• Knowledge of AI governance and responsible AI practices in enterprise settings: Familiarity with model risk management, bias evaluation, audit logging, and enterprise AI governance frameworks and experience working alongside governance or compliance teams to get AI systems approved for production use.
Who you are?
• A builder first : you are most energized when something tangible exists that didn't exist before
• Equally fluent in the language of healthcare operations and the language of AI engineering and able to switch between them in the same meeting
• Someone who earns trust through working software, not promises you show progress, you don't just report it
• Deeply curious about what AI can do in healthcare and intellectually honest about where it falls short
• Comfortable with ambiguity, urgency, and high stakes you thrive when the path is unclear and the expectation is still high