Principal Technical Product Manager

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together.

Optum AI is UnitedHealth Group's enterprise AI team. We are AI/ML scientists and engineers with deep expertise in AI/ML engineering for health care. We develop AI/ML solutions for the highest impact opportunities across UnitedHealth Group businesses including UnitedHealthcare, Optum Financial, Optum Health, Optum Insight, and Optum Rx. In addition to transforming the health care journey through responsible AI/ML innovation, our charter also includes developing and supporting an enterprise AI/ML development platform.

As a product leader within the enterprise AI Platforms team in the Chief AI Office, you will own the product strategy and execution for a commercial AI platform
- the secure, PHI-ready model access layer, the capability gateway that makes licensed intelligence callable from any approved agent or application, and the agent harness those agents run on. Your job is to decide what that platform becomes as a commercial product: what is packaged and sold, how it is priced and metered, what the platform commits to and for how long, and what it will deliberately not do.

This is a technical product management role, paired with an engineering organization who owns the technical architecture and build of the same platform. You will own what the platform commits to and why
- roadmap, interface contracts, evaluation criteria and service levels. You will work directly with business and design partners on what is actually worth building, carry the business case through the capital funding process, align the commercial roadmap with the enterprise multi-platform strategy, and be accountable for measured outcomes: adoption, reuse, time to value and unit economics. Expect significant influence over platform direction and a short path between a design partner conversation and a change in the roadmap.

Optum AI team members:

• Have impact at scale: We have the data and resources to make an impact at scale. When our solutions are deployed, they have the potential to make health care system work better for everyone
• Do ground-breaking work: Many of our current projects involve cutting edge ML, NLP and LLM techniques. Generative AI methods for working with structured and unstructured health care data are continuously being developed and improved. We are working in one of the most important frontiers of AI/ML research and development
• Partner with world-class experts on innovative solutions: Our team members are developing novel AI/ML solutions to business challenges. In some cases, this includes the opportunity to file patents and publish papers about the methods we develop. We also collaborate with AI/ML researchers at some of the world's top universities

You’ll enjoy the flexibility to work remotely
* from anywhere within the U.
S. as you take on some tough challenges. For all hires in the Minneapolis or Washington, D.
C. area, you will be required to work in the office a minimum of four days per week.

Primary

Responsibilities:

• Own the product strategy, roadmap and measured outcomes for the commercial AI platform: secure, PHI-ready model access with favorable inference economics, the capability gateway that makes licensed intelligence callable from any approved agent or application, and the agent runtime those agents run on
• Define the commercial shape of the platform
  - what ships as a product versus what is delivered as a service, SKU and tier definitions, entitlement models, metering, and pricing mechanics that hold margin as underlying inference costs move
• Translate client demand, market signal and internal partner needs into a single prioritized backlog, and write requirements at a technical altitude engineers can build against: API and tool contracts, schemas, versioning and deprecation policy, conformance expectations, and SLOs
• Treat developer experience as an explicit product concern, with owned measures for time to first successful call, documentation and reference implementation quality, sandbox and test data access, and support and escalation paths
• Build and defen