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WelbeHealth is a value-based healthcare organization that's transforming the future of senior care by providing an all-inclusive care option to our most vulnerable senior population.

The Director, AI Engineering & Innovation provides strategic and technical leadership for WelbeHealth's artificial intelligence and innovation program. This role is responsible for defining and executing an AI product roadmap that directly advances participant outcomes and operational excellence within our PACE model of care. The Director, AI Engineering & Innovation translates WelbeHealth's mission into a portfolio of AI-powered solutions — overseeing their end-to-end delivery from ideation through production — while leading and developing a team of AI Engineers. The Director serves as a senior thought partner to cross[1]functional stakeholders, ensures all AI initiatives meet healthcare regulatory requirements, and makes informed build-versus-buy decisions across the AI vendor landscape. The Director, AI Engineering & Innovation is a member of the WelbeHealth leadership team and facilitates collaborative relationships across WelbeHealth and with external stakeholders to promote WelbeHealth values, team culture and mission.

We care about our team members. That's why we offer:

• Medical insurance coverage (Medical, Dental, Vision)
• Work/life balance - We mean it! 17 days of personal time off (PTO), 12 holidays observed annually, and 6 sick days
• 401K savings + match
• Comprehensive compensation package including base pay and bonus
• And additional benefits!

On the day-to-day, you will:

• AI Product Roadmap: Define, prioritize, and maintain a multi-horizon AI innovation roadmap aligned to WelbeHealth's mission of unlocking the full potential of our most vulnerable seniors.
• Cross-Functional Stakeholder Alignment: Partner with clinical, operations, compliance, and technology leaders to identify high-impact AI opportunities, secure organizational alignment, and champion adoption of AI-powered solutions across the enterprise.
• Build vs. Buy Decision Authority: Evaluate and recommend make-versus-partner decisions across the AI and technology vendor landscape. Lead vendor assessments, contract negotiations, and ongoing governance for third-party AI tools and platforms.
• Innovation Scouting: Continuously monitor the evolving AI landscape — frontier models, agentic frameworks, retrieval systems, and healthcare-specific AI capabilities — and proactively recommend emerging approaches that can improve participant outcomes, operational efficiency, or team productivity.
• AI Solution Delivery: Oversee the full development lifecycle for AI use cases — from rapid proof-of-concept through validation, iteration, and production deployment. Maintain accountability for delivery quality, timelines, and technical standards across the AI engineering portfolio.
• Architecture Guidance: Provide hands-on technical direction for AI application architecture, including retrieval-augmented generation (RAG) pipelines, agentic workflows, enterprise LLM integration, and secure cloud deployment patterns (primarily Azure).
• Healthcare Compliance: Ensure all AI systems and data practices adhere to HIPAA, PHI handling requirements, and the compliance standards unique to healthcare technology. Partner with legal, compliance, and security teams to embed privacy-by-design principles into every AI solution.

Job requirements include:

• Bachelor's Degree required in Computer Science, AI, Computer Engineering, or other relevant field; Master's Degree preferred
• Minimum of five (5) years of hands-on experience in AI/ML engineering, applied AI development, or software engineering with a strong AI focus, including at least two (2) years in a technical leadership or people management role.
• Strategic leadership: Demonstrated ability to define and execute a technology or AI product roadmap, align cross-functional stakeholders, translate business and organizational goals into a sequenced portfolio of deliverable initiatives, and present complex technical solutions to non-technical audiences.
• Enterprise LLM & AI application expertise: Proven track record designing, building, and deploying production-grade enterprise AI/LLM solutions on commercial platforms (OpenAI/Azure OpenAI, Anthropic Claude, Google Gemini), including prompt engineering, RAG pipelines, agentic frameworks and workflows, AI assistants, and multi[1]model orchestration.
• Cloud & infrastructure: Hands-on experience architecting and deploying AI services in secure cloud environments — primarily Azure (Azure OpenAI / Azure AI); AWS a plus — with a focus on scalability, reliability, and cost. Includes Docker, private networking, managed identities, and DevOps/CI/CD pipelines.
• Python & technical depth: Advanced proficiency in Python for AI development, with a strong software engineering background including API and service integration. Ability to engage credibly in hands-on technical design and code review with engineering staff.