Senior Agentic AI Engineer

At Optum, you’ll help build scalable, secure, and compliant agentic AI solutions that support healthcare consumer experiences. This role combines end-to-end delivery with production-grade engineering, including LLM and automation workflows, evaluation and testing, and cross-functional collaboration. If you like turning ambiguous requirements into reliable systems that can ship, this is a strong fit.

What you’ll do

• Design agentic solutions aligned to healthcare industry requirements, with security and compliance built in
• Architect end-to-end systems integrating LLMs, machine learning models, APIs, and enterprise platforms
• Evaluate trade-offs (for example: build vs. orchestrate, model selection, and latency vs. accuracy) and communicate recommendations to stakeholders
• Deliver production-ready AI applications, including LLM-based workflows, copilots, and intelligent automation
• Integrate AI agents and automation into client environments to optimize for performance, scalability, and reliability
• Prototype quickly to validate concepts, iterate with client feedback, and accelerate time-to-value
• Troubleshoot complex issues across distributed systems and cloud platforms
• Build and maintain evaluation datasets, scoring rubrics, agent-performance tests, and failure-mode analysis tools
• Bridge business, clinical, and technical perspectives to ensure alignment and clarity across groups
• Collaborate with product, platform, and engineering teams to bring reusable capabilities into client deployments
• Communicate complex technical concepts in an actionable way for non-technical stakeholders
• Drive end-to-end client solutions from discovery through production deployment, translating ambiguous needs into scalable, high-impact outcomes
• Build trusted advisor relationships with client stakeholders and contribute repeatable consulting and engineering patterns across engagements
• Design prototypes with a clear path to production, including supportability and transition to production engineering teams

Requirements

• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field
• 5+ years of hands-on software engineering experience deploying distributed systems and cloud-native solutions
• 5+ years of engineering experience with strong proficiency in Python (or equivalent)
• Experience building and deploying AI/ML solutions, including familiarity with LLMs, prompt engineering, and model deployment patterns
• Experience structuring ambiguous problems into clear, actionable solutions
• Experience using infrastructure as code in cloud environments, especially Azure
• Proficiency with modern development frameworks, APIs, and data integration approaches
• Advanced knowledge and experience with AI-DLC
• Proven ability to lead client engagements across discovery, solution design, and delivery
• Proven stakeholder management skills, with influence across technical and executive audiences

Technologies you may use

Python, LLMs, machine learning models, APIs, AI/ML, prompt engineering, infrastructure as code, Azure, React, NextJS, Adobe Experience Platform

Benefits

• Comprehensive benefits package
• Incentive and recognition programs
• Equity stock purchase
• 401k contribution (subject to eligibility requirements)

Remote work

Remote work from anywhere within the U.S. For hires in the Minneapolis or Washington, D.C. area, required to work in the office a minimum of four days per week. All employees working remotely must adhere to UnitedHealth Group’s Telecommuter Policy.

Compensation

Salary for this role ranges from $120,100 to $214,500 annually, based on full-time employment and factors including local labor markets, education, work experience, and certifications.

Additional details

This posting will be live for a minimum of 2 business days or until a sufficient candidate pool has been collected. It may come down early due to applicant volume.