[Hiring] Senior Principal AI/ML Engineer @UnitedHealth Group

Role Description

As the Senior Principal AI/ML Engineer for GTS, you will drive the architectural vision, technical design, and hands-on delivery of scalable, resilient, and secure software and artificial intelligence/machine learning (AI/ML) solutions that support healthcare applications and workflows. Your contributions here have the potential to change lives.

• Define architecture for complex initiatives spanning multiple teams.
• Turn business needs into technical designs, phased delivery plans, and measurable quality goals while resolving dependencies, technical risks, and competing design priorities.
• Design and build distributed, cloud-native services, robust APIs, reusable libraries, and shared platforms.
• Create working prototypes, evaluate design alternatives, and lead technical and code reviews.
• Build reliable data integrations and event-driven workflows.
• Advance continuous integration and continuous delivery (CI/CD), infrastructure as code (IaC), and automated security and quality checks.
• Own production readiness and ongoing technical health.
• Optimize performance, scalability, resilience, and cloud cost.
• Influence technical roadmaps and engineering standards across GTS.
• Develop and integrate machine learning and large language model (LLM) solutions.
• Build AI agents with orchestration, tool calling, and guardrails.
• Establish model, prompt, and retrieval evaluations using representative datasets and clear acceptance criteria.
• Implement machine learning and LLM operations (MLOps/LLMOps) pipelines.
• Guide adoption of AI-powered development tools and cloud AI services.
• Partner with product, data, security, and business leaders on responsible AI delivery.

Qualifications

• Bachelor’s degree in computer science, software engineering, a related technical field, or equivalent practical experience.
• 15+ years of relevant engineering experience, including 10+ years of hands-on software engineering and 6+ years delivering production AI/ML solutions.
• Hands-on depth in cloud-native architecture, automated testing, CI/CD, IaC, observability, secure design, performance tuning, and production incident resolution.
• Demonstrated ability to integrate and evaluate ML and LLM solutions, including generative AI, RAG, and agents.
• Demonstrated delivery of complex, production-grade distributed services, APIs, data integrations, and reusable platforms.
• Evidence of cross-team technical leadership on ambiguous initiatives.

Requirements

• Strong coding skills in Python and at least one additional general-purpose language.

Preferred Qualifications

• Experience with healthcare applications, clinical or administrative workflows, sensitive health data, or other regulated environments.
• Experience with one or more major cloud platforms and managed AI services, such as Azure, Amazon Web Services, or Google Cloud.
• Experience with relevant tools such as PyTorch, TensorFlow, scikit-learn, agent orchestration frameworks, vector databases, containers, and Kubernetes.
• Experience scaling shared engineering or AI platforms across teams.

Benefits

• Comprehensive benefits package.
• Incentive and recognition programs.
• Equity stock purchase and 401k contribution.

Application Deadline

This will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected.