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.
Help build the enterprise AI runtime and agentic platform that will power AI solutions across Optum.
AI Factory Runtime and Agentic Platform Services provides a secure, scalable platform that enables engineering teams to deploy and operate AI workloads and agents across private cloud, public cloud, and hybrid environments.
As Principal Technical Product Manager - AI Runtime, Agentic Platform & Compute, you will own the product strategy for this critical layer of AI Factory. You will transform GPU compute, Kubernetes, model serving, inference, agent runtimes, agent orchestration, multi-agent execution, lifecycle management, and observability into enterprise services that development teams can easily consume.
You will define the product vision, roadmap, service model, and investment priorities while partnering with Engineering, Compute, Cloud, Security, Governance, Risk, Compliance, and Architecture leaders to build a high-performance enterprise AI platform.
This role owns the AI runtime, compute, and operational agent platform experience. It does not own underlying physical infrastructure, enterprise model approval and Responsible AI policy processes, or the business-specific agents, AI applications, and solutions built by consuming teams.
AI can only scale across the enterprise when engineering teams have secure, reliable, and easy-to-consume runtime and agent platform capabilities beneath their solutions.
You will turn advanced GPU, Kubernetes, AI runtime, and agent execution technologies into standardized enterprise services that help teams move AI workloads and agents into production faster, while integrating with enterprise-approved model access, security, and governance services.
This is an opportunity to shape a foundational AI platform serving one of the world's largest healthcare enterprises and influence how engineering teams securely deploy and operate AI workloads and agents at enterprise scale.
Primary Responsibilities:
- Own the product vision, strategy, roadmap, and investment priorities for AI Factory Runtime and Agentic Platform Services across private cloud, public cloud, and hybrid environments
- Define clear product boundaries, ownership, and integration points across AI Factory, Compute, Cloud, Security, Governance, Architecture, enterprise AI enablement services, and consuming AI solution teams
- Productize GPU compute, Kubernetes/OpenShift, model serving, LLM inference, agent runtimes, agent orchestration, multi-agent execution, agent lifecycle management, and platform APIs into standardized services engineering teams can easily consume
- Define the roadmap and service model for operational agent platform capabilities, including agent deployment, execution, orchestration, scaling, lifecycle management, observability, tool connectivity, and governance integration
- Create a leading developer experience, including self-service onboarding, service tiers, APIs, SLOs/SLAs, documentation, consumption models, and platform automation
- Develop a deep understanding of AI workload, agent workload, and customer requirements and translate them into platform capabilities, architecture priorities, and measurable business outcomes
- Partner with engineering and architecture teams to evolve AI runtime and agent platform capabilities across private cloud, Azure, AWS, GCP, and hybrid environments while abstracting infrastructure complexity from consumers
- Partner with Security, Governance, Risk, and Compliance teams to incorporate security, privacy, Responsible AI, observability, and governance requirements into platform services without duplicating enterprise policy, model approval, or governance ownership
- Partner with Compute and Cloud Engineering to understand workload demand and improve GPU utilization, capacity efficiency, platform performance, reliability, and cost effectiveness
- Drive enterprise adoption and measure success through outcomes such as time-to-first-workload, time-to-first-agent, platform utilization, reliability, onboarding speed, adoption, and customer satisfaction
- Influence senior technology leaders and drive decisions across competing customer, engineering, architecture, security, operational, and investment priorities
- Technology Environment
- This role will influence a modern enterprise AI runtime and agentic platform incorporating technologies and practices such as:
- Kubernetes and Red Hat OpenShift
- NVIDIA GPU platforms
- GPU-enabled container workloads
- AI model serving and inference
- Agent runtimes
- Agent orchestration and multi-agent execution
- Agent lifecycle management
- Tool and API connectivity
- Public and private cloud
- APIs and automation
- GitOps
- Observability and telemetry
- Platform engineering
- Experience with every technology is not expected. We are looking for someone with strong platform fundamentals who can rapidly understand emerging AI and agentic technologies and translate them into enterprise products
- Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so
Required Qualifications:
- 10+ years of experience across technical product management, platform engineering, cloud infrastructure, architecture, or related technology leadership roles, including significant product ownership or product leadership experience
- Experience owning, designing, or shaping an enterprise platform, developer platform, cloud service, Kubernetes platform, distributed compute platform, agent platform, or comparable technology product
- Experience defining product strategy, roadmaps, service models, SLOs/SLAs, adoption metrics, consumption models, and investment priorities
- Solid understanding of Kubernetes/container platforms, cloud infrastructure, distributed systems, platform engineering, or GPU/AI compute architectures
- Demonstrated ability to translate complex infrastructure, runtime, and agent platform capabilities into simple, consumable platform products and developer experiences.
- Demonstrated ability to communicate complex platform strategies to executive audiences and influence senior engineering, architecture, security, product, and business leaders without direct authority
- Proven ability to build consensus and make trade-offs across competing customer, engineering, architecture, security, operational, and business priorities
Preferred Qualifications:
- Advanced degree in Computer Science, Engineering, Data Science, Business, or a related discipline
- Experience with AI/ML infrastructure, GPU compute, model serving, LLM inference, agent runtimes, agentic platforms, agent orchestration frameworks, multi-agent systems, or AI runtime platforms
- Experience with Kubernetes, Red Hat OpenShift, NVIDIA GPU technologies, or other large-scale container and accelerated-compute environments
- Experience with enterprise AI or cloud AI platforms such as Azure AI Foundry, AWS Bedrock, Google Vertex AI, Databricks, or similar technologies
- Experience with agent deployment, execution, orchestration, lifecycle management, observability, or tool connectivity patterns
- Experience building platforms spanning private cloud, public cloud, and hybrid environments
- Experience with developer self-service, platform engineering, observability, capacity management, FinOps, or AI governance integration
- Experience delivering technology platforms within large-scale or highly regulated enterprises
The Candidate We're Looking For
- The solid candidate will think of infrastructure, runtime, and agent platform capabilities as products rather than simply technologies.
- You should be comfortable moving between AI workloads, agent workloads, GPU compute, Kubernetes, APIs, developer experience, platform economics, and executive strategy without needing to be the deepest engineer in every technology.
- You enjoy taking complex infrastructure and agent platform capabilities and making them simple for developers to consume. You can make decisions while technology and customer requirements are changing rapidly, and influence a large organization through technical credibility, product thinking, and a clear vision for where the platform needs to go.
At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.