Head of Technical Product Management

Role overview Set the technical product direction for a cloud data and AI platform serving health plans, and lead the product management organization responsible for delivering it. Reporting to the CTO, this executive-level role partners with engineering and company leaders to connect platform strategy, architecture, compliance, and investment decisions to customer and business outcomes.

Responsibilities - Define and communicate a multi-year technical roadmap for cloud data and AI infrastructure in partnership with the CTO and executive team. - Lead the product portfolio across healthcare data ingestion, lakehouse architecture, data products, and AI/ML tooling; guide sequencing and build, buy, or partner decisions. - Work with engineering leaders on cloud infrastructure, distributed systems, APIs, and AI platform architecture, explaining key trade-offs. - Set outcome measures for adoption, reliability, performance, delivery quality, service levels, cloud economics, and return on investment. - Establish standards for data quality, AI governance, healthcare compliance, identity and access, and observability. - Build and scale a technical product management function, including its leadership team and operating practices.

Requirements - Bachelor’s or master’s degree in a technical discipline such as computer science, data science, engineering, or mathematics. - 15+ years in technical product management, including 6+ years leading platform, cloud, SaaS, or data/AI infrastructure products at scale. - 8+ years of people leadership, including leading managers and building effective product management organizations. - Experience creating or scaling a technical product management function within engineering, including hiring, role levels, operating model, and career development. - Track record of influencing executives and owning portfolio strategy and outcomes. - Strong working knowledge of modern cloud data platforms and data engineering; experience delivering machine learning or generative AI products and familiarity with evaluation and governance frameworks.

The source also calls for close partnership with engineering on software delivery quality and velocity. Its requirements section is truncated, so further qualifications may apply.