Lead AI/ML Engineer: Hybrid in Minnesota or DC, Remote elsewhere at UnitedHealth Group Canada

Eden Prairie, Minnesota, United States -

Full Time

Start Date

Immediate

Expiry Date

07 Jun, 26

Salary

193200.0

Posted On

09 Mar, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

AI System Design, Multi-Agent Systems, LLMs, LangChain, AutoGen, Semantic Kernel, Voice AI, ML Model Deployment, Azure, Python, PyTorch, Hugging Face, Scikit Learn, Spring Boot, RAG, Vector Search

Industry

Hospitals and Health Care

Description

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. Come build the AI foundation behind SGS, a modern platform where multi agent systems can reason, plan, and safely connect to enterprise tools to turn conversations, documents, and network signals into action. In this role, you will own the architecture for the capabilities customers feel every day, including real time voice translation, voice based assessments, and call quality audits that help teams respond faster and follow the right procedures. You will also advance Document AI and our Virtual Investigator to accelerate intake, surface risk early, and turn complex investigative questions into clear, explainable answers. On the fraud side, you will combine real time ML with graph analytics to detect emerging hotspots, uncover collusive networks, and stop improper payments before they happen, then translate that intelligence into AI generated insights and KPI visibility leaders can use immediately. You will set the technical direction for orchestration and governance on Azure, raise engineering standards across product lines, and mentor a globally distributed team that ships to production. If you want deep ownership, high stakes impact, and the chance to define how agentic AI operates at scale, you will thrive here. You’ll enjoy the flexibility to work remotely * from anywhere within the U.S. as you take on some tough challenges. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week. Primary Responsibilities: Lead AI System Design: Architect and evolve our multi-agent AI platforms, enabling agents to reason, plan, and interact with external tools via LLMs and modular service layers Technical Ownership: Define standards, best practices, and technical vision for AI orchestration across product lines including voice agents, fraud detection, and agentic workflows Multi-Agent Frameworks: Guide adoption of frameworks like LangChain, AutoGen, and Semantic Kernel; integrate emerging protocols such as Model Context Protocol (MCP) to scale tool and agent interoperability AI Interface Innovation: Lead the design of agentic user experiences, enabling LLMs to act as intelligent interfaces to enterprise tools and APIs Voice AI Strategy: Architect full-stack voice agent pipelines - from ASR and multi-turn dialogue to TTS and telephony integrations (SIP, Twilio, etc.) ML & Fraud Systems: Oversee development and deployment of ML models for fraud and anomaly detection, emphasizing scalability, explainability, and real-time responsiveness Cloud-Native Engineering: Lead AI/ML system deployment using Azure OpenAI, Azure Functions, Event Hubs, Cognitive Search, Cosmos DB, and other cloud-native tools Mentorship & Delivery: Guide senior and junior engineers, lead architecture reviews, and drive cross-team technical delivery in a globally distributed environment AI Governance & MLOps: Set standards for experimentation, monitoring, CI/CD pipelines, and lifecycle management of LLM and ML models You’ll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in. Required Qualifications: Bachelor’s degree or higher in Computer Science, Engineering, or related field, or equivalent professional experience 8+ years building production software, including 3+ years as a technical lead for AI or ML product development (ownership from design through launch) 5+ years professional Python experience and hands on use of ML or NLP libraries such as PyTorch, Hugging Face, or scikit learn, including deploying models or pipelines to production 3+ years hands on building and operating Spring Boot microservices in production, including API design, automated testing, CI/CD, and on call or incident participation Agentic and LLM systems: Proven shipped at least one LLM based system to production that uses tool calling or function calling to interact with external services or enterprise APIs, with defined evaluation and monitoring RAG and vector search: Proven built and shipped retrieval augmented generation or semantic search solutions using vector search, embeddings, and external knowledge integration (for example Azure Cognitive Search or comparable tooling) Azure architecture: Proven built and deployed production workloads on Azure, using multiple services such as Azure OpenAI, Azure Functions, Event Hubs, Cognitive Search, and Cosmos DB, with security, observability, and cost considerations Preferred Qualifications: LLM evaluation and regression testing: Experience building automated evaluation harnesses for LLM and agent workflows, including golden datasets, offline and online testing, and measurable quality metrics (for example task success rate, groundedness, or human review agreement) Responsible AI and adversarial testing: Hands on experience with prompt injection and data exfiltration testing, safety reviews, and implementing guardrails to reduce hallucinations and unsafe outputs in production Production observability for agents: Proven implemented end to end monitoring for agentic systems, including distributed tracing, tool call success rates, latency and error budgets, and token and cost telemetry with actionable alerting Security for tool calling and AI systems: Proven designed secure patterns for tool enabled agents, including least privilege access, secrets management, and policy based controls for tool/API execution (for example OAuth scopes, managed identity, and audit logging) Platform scale and efficiency: Proven ability to optimize LLM or voice system performance and cost using techniques such as caching, batching, streaming responses, rate limiting, model routing, and fallback strategies *All employees working remotely will be required to adhere to UnitedHealth Group’s Telecommuter Policy Pay is based on several factors including but not limited to local labor markets, education, work experience, certifications, etc. In addition to your salary, we offer benefits such as, a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements). No matter where or when you begin a career with us, you’ll find a far-reaching choice of benefits and incentives. The salary for this role will range from $112,700 to $193,200 annually based on full-time employment. We comply with all minimum wage laws as applicable. Application Deadline: This will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected. Job posting may come down early due to volume of applicants. At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone–of every race, gender, sexuality, age, location and income–deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes — an enterprise priority reflected in our mission. UnitedHealth Group is an Equal Employment Opportunity employer under applicable law and qualified applicants will receive consideration for employment without regard to race, national origin, religion, age, color, sex, sexual orientation, gender identity, disability, or protected veteran status, or any other characteristic protected by local, state, or federal laws, rules, or regulations. UnitedHealth Group is a drug - free workplace. Candidates are required to pass a drug test before beginning employment. #OptumTechPJ

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Responsibilities

This role involves architecting and evolving multi-agent AI platforms that use LLMs to reason, plan, and interact with external tools, while also defining technical standards for AI orchestration across product lines like voice agents and fraud detection. The lead will oversee the development of ML models for fraud detection and guide the deployment of AI/ML systems using Azure cloud-native tools, alongside mentoring a globally distributed engineering team.