Principal AI or ML Engineer

About the role

Optum, part of UnitedHealth Group, is looking for a Principal AI/ML Engineer in Hyderabad to build an end-to-end AI lifecycle governance system. The role connects intake and registration, automated governance gating, request routing and runtime observability and monitoring, closing the loop between pre-production governance and post-production monitoring, alerting, feedback and containment. It is a system-design role that defines how the capabilities integrate and leads the hands-on engineering teams that deliver them.

Key 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 between pre-production governance and post-production monitoring, alerting, feedback and containment.
• Define data flows, interfaces and contracts between components to support lifecycle traceability.
• Build and implement core integration components hands-on, and lead low-level design and the breakdown of architecture into engineering tasks.
• Lead and influence senior engineers and architects across teams, drive architectural consensus and resolve design disagreements, acting as the technical escalation point for integration decisions.
• Work with teams owning intake, governance, routing and observability to align on integration design and sequencing, and identify and close architectural gaps that could put enterprise AI audit commitments at risk.
• Set technical direction and review designs and code to keep the integrated system consistent.

Required profile

• Bachelor's degree or higher in computer science or a 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 deliver shared architecture.
• Demonstrated ability to lead and influence senior engineers and architects without direct reporting authority, and to work independently on undefined problems.

Required skills

• Demonstrated experience in AI platform architecture.
• Solid Python skills, including building production-grade services and integrations.
• Preferred: AI observability, evaluation or testing platforms; automated governance gating or policy-as-code; human-in-the-loop review and feedback mechanisms; enterprise AI audit or risk management frameworks.