Principal AI or ML Engineer

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. Our enterprise AI organization builds platforms that govern and operate AI systems across the business, spanning intake and registration, automated governance gating, request routing, and runtime observability and monitoring. Today, these capabilities operate as distinct components across the AI lifecycle. We need to connect them end-to-end - linking pre-production governance to post-production monitoring, alerting, feedback, and containment - to meet enterprise AI risk management commitments and committed audit-related deliverables.

As a Principal AI/ML Engineer, you will architect and build the end-to-end AI lifecycle governance system connecting intake/registration, automated governance gating, request routing, and runtime observability/monitoring. This is a system-design role: you will define how these capabilities integrate, close the loop between pre-production governance and post-production monitoring/containment, and build the technical foundation the current team does not yet have in place. You will work across teams to design the integration points and lead the hands-on engineering teams to deliver them.

Primary Responsibilities

• Architect the end-to-end AI lifecycle governance system linking intake/registration, automated governance gating, request routing, and runtime observability/monitoring
• Design the technical integration connecting pre-production governance (intake, automated gating) with post-production monitoring, alerting, feedback, and containment
• Define data flows, interfaces, and contracts between system components to support lifecycle traceability
• Build and implement core integration components hands-on, not limited to design
• Lead low-level design activities and break down architecture into executable engineering tasks
• Lead and influence senior engineers and architects across teams to align on a shared technical direction, without formal reporting authority over those teams
• Drive architectural consensus across intake, governance, routing, and observability teams, resolving design disagreements between senior engineers where priorities conflict
• Serve as the technical point of escalation for cross-platform integration decisions, influencing senior stakeholders through sound design rationale rather than positional authority
• Work directly with teams owning intake/registration, automated governance gating, request routing, and observability/monitoring to align on integration design and sequencing
• Identify and close architectural gaps that put enterprise AI audit commitments at risk
• Set technical direction and review designs/code to maintain consistency across the integrated system
• Comply with all applicable Company policies, procedures, and business directives, changes including those relating to work location, team assignments, work schedules, and flexible work arrangements

Required Qualifications

• Bachelor’s degree or higher in computer science or related field
• Solid hands-on experience in AI/ML engineering, including building and integrating production AI systems
• Experience designing systems involving governance, monitoring, or lifecycle management of software/AI systems
• Experience working across multiple engineering teams to align on and deliver shared architecture
• Demonstrated experience in AI platform architecture - designing systems that span multiple components/services
• Solid Python skills, including building production-grade services and integrations
• Demonstrated ability to lead and influence senior engineers and architects across teams through technical credibility, in the absence of direct reporting authority
• Demonstrated ability to operate independently on ambiguous, undefined problems - this role is building something that does not yet exist on the team

Preferred Qualifications

• Experience with AI observability, evaluation (evals), or test…