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As Humana continues its transformation into an AI-first enterprise, we seek a hands-on, technically proficient Lead Product Manager to accelerate the design, prototyping, and scaling of advanced AI solutions across our business. In this role, you will collaborate with engineers, data scientists, and business leaders to identify opportunities, architect AI-driven solutions—including those leveraging state-of-the-art LLMs and GenAI—and drive them through Humana’s enterprise AI governance process, from ideation to value realization. You will be empowered to both lead and build, applying deep technical expertise while ensuring responsible, governed, and scalable delivery of AI capabilities.

Enterprise Context

Humana is a member-focused healthcare company committed to transforming insurance and care delivery—spanning Insurance, Pharmacy, Home Health, and Clinics—through technology and innovation. As the organization undergoes a significant transformation into a more efficient, technology-enabled operation, AI is positioned as a foundational driver of this change.

Humana’s enterprise AI program is structured to ensure strategic alignment, robust governance, and value realization across business segments. The program features cross-functional leadership from Corporate Strategy, Finance, Law/Risk/Compliance, and Data & Digital, with a Responsible AI Council (RAIC) overseeing solution design, technical standards, and responsible AI practices. Business teams collaborate with technology and program leaders to advance high-value use cases through a structured stage-gate process—from ideation and business case validation to pilot, scale, and management. All AI initiatives are evaluated for business impact, compliance, and scalability, with centralized and segment funding focused on delivering measurable value to members, associates, and leaders.

Key Responsibilities

• End-to-End Technical Product Leadership:
  Drive technical product vision, solution architecture, and hands-on prototyping for a major AI product area. Own product outcomes from discovery through pilot, scale, and ongoing optimization.
• Build and Prototype AI Solutions:
  Design and co-develop working prototypes and production-ready components using leading AI/ML tools and platforms (e.g., Python, TensorFlow, PyTorch, Hugging Face, LangChain, Azure AI, OpenAI). Rapidly iterate on LLM-based applications, conversational AI, and intelligent automation.
• Business Engagement & Translation:
  Partner directly with business stakeholders to deeply understand operational challenges, map complex processes, and translate them into actionable AI use cases with clear success metrics.
• Enterprise Governance Compliance:
  Guide AI solutions through Humana’s multi-stage governance process—including AIRB, LRC, and Responsible AI reviews—by preparing technical documentation, scorecards, and market scans, and leading technical deep dives at each stage gate.
• Solution Evaluation & Benchmarking:
  Develop and apply robust evaluation frameworks to benchmark AI models, compare platform options, and ensure solutions meet business, technical, and regulatory standards.
• Reusable Frameworks & Best Practices:
  Author and maintain code libraries, reusable solution patterns, and technical playbooks to enable rapid, consistent AI delivery across multiple business lines.
• Mentor and Enable Teams:
  Provide technical mentorship to product managers, engineers, and data scientists; foster a culture of hands-on experimentation and continuous learning.
• Stakeholder Communication:
  Communicate technical strategy, risks, and business value clearly and effectively to executive, business, and technical audiences.

Use your skills to make an impact

Required Qualifications

• B.S. or M.S. in Computer Science, Engineering, or a related field (or equivalent experience)
• 7+ years of relevant experience, with at least 3 years in technical product management or engineering roles focused on AI/ML solutions.
• Demonstrated ability to architect, build, and scale AI applications (including LLM-based solutions) in an enterprise environment.
• Hands-on expertise with AI/ML tools, frameworks, and cloud platforms (Python, PyTorch/TensorFlow, LangChain, vector databases, RAG architectures, prompt engineering, Azure/OpenAI, etc.).
• Experience with the full lifecycle of AI products: requirements…