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.
