AI/ML Engineer - AI and Java Spring

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. Join our team as a Grade 27 Software Engineer, where you’ll drive innovation in AI-powered solutions and claims testing automation. We’re looking for a technical leader with deep expertise in Python, generative AI, and modern DevOps practices, ready to architect scalable applications and automate critical business processes.

Primary Responsibilities

• Architect, develop, and deploy large-scale AI and data-driven applications using Python and relevant frameworks
• Lead the design and implementation of agentic AI workflows, prompt engineering, and retrieval augmented generation (RAG) patterns
• Integrate generative AI solutions with enterprise databases (PostgreSQL, Oracle, Vector DBs like ChromaDB) and cloud platforms
• Build and optimize CI/CD pipelines (GitHub Actions, Jenkins) for production-scale deployment and reliability
• Collaborate with cross-functional teams to deliver AI-powered features, including natural language querying, data comparison, and visualization
• Develop automation scripts and utilities to streamline data processing, archiving, and system maintenance
• Establish and enforce best practices in code review, testing, and documentation for AI and data engineering projects
• Participate in customer presentations, handle critical issues, and provide technical insights on AI solutions
• Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regard to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so

AI Builder Responsibilities

• Use approved GenAI tools, including Copilot or equivalent enterprise-authorized tools, to accelerate ideation, code generation, test generation, documentation, debugging, and productivity improvements
• Apply AI-assisted development techniques responsibly to improve code clarity, maintainability, testability, and engineering flow while validating outputs before use
• Develop scripts, utilities, workflow automations, and internal productivity accelerators that reduce repetitive work and improve engineering effectiveness
• Follow responsible AI, privacy, security, intellectual property, and data handling expectations when using AI tools
• Stay current with emerging GenAI engineering practices, prompt patterns, agentic workflows, and AI-enabled SDLC opportunities relevant to assigned products

Builder Responsibilities

• Design, develop, and deploy AI-enabled or automation-enabled solutions using approved no-code, low-code, and advanced engineering platforms where they create measurable value
• Translate business needs into fit-for-purpose technical solutions that improve product capabilities, workflows, decision support, operational efficiency, or developer productivity
• Prototype quickly, validate assumptions with stakeholders, and convert successful prototypes into maintainable, secure, and scalable solutions
• Design and implement automated claims testing solutions, leveraging Python and AI to validate claims processing workflows and ensure accuracy
• Develop and maintain test automation frameworks for claims-related systems, integrating with CI/CD pipelines for continuous testing
• Collaborate with QA and business analysts to define test cases, automate regression testing, and monitor test coverage
• Analyze claims data using AI and machine learning techniques to identify anomalies, optimize processing, and improve system reliability
• Provide technical leadership in claims testing automatio…