Sr. AI​/ML Engineer- Remote or Eden Prairie, MN

Job d:

Location:

Eden Prairie, Minnesota, United States Salary: $120,100 - $214,500/year

Job Area:
Technology Company:
United Health Group 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.

As a Sr AI/ML Engineer on the United AI Studio team, you will build agentic experiences on an enterprise AI platform-including Agents, Model Context Protocol (MCP) servers, plugins, and skills that enable teams to register, discover, and govern AI assets. You will build agents that eliminate friction across engineering workflows, starting with responsible AI reviews. You will join a team running AI Solution governance, AI Catalog, and enterprise-wide agent/skill registries, working alongside teams building underlying governance rails to deliver cutting-edge AI capabilities across the organization.

You'll enjoy the flexibility to work remotely
* from anywhere within the U.S. as you take on some tough challenges.

Primary Responsibilities:

Design, develop, and deploy AI-powered solutions to address complex business challenges with an emphasis on responsible use of AIBuild agentic experiences end-to-end, managing tool design, context and state management, failure handling, retries, and cost/latency budgets from prototype through production behind enterprise gateways

Design orchestration architectures, choosing between single agents, subagents, and deterministic pipelines, evaluating when a workflow should or should not be agentic

Expose AI capabilities through channel-agnostic APIs and Model Context Protocol (MCP) tools with required authentication, scoping, and auditability

Deliver agentic experiences into enterprise search and chat surfaces (e.g., Teams, Slack, Glean) using bot frameworks, connectors, and APIsStand up evaluation harnesses for agent behavior using golden task sets, trajectory/end-state scoring, LLM-as-judge calibrated against human labels, and regression suites integrated into CI/CD pipelines

Instrument production agents with tracing across tool calls, token/cost telemetry, and failure taxonomies, feeding real traces back into evaluation sets

Test agents adversarially against prompt injections and tool output vulnerabilities, implementing necessary remediations

Leverage enterprise-approved AI coding tools to streamline workflows, automate engineering tasks, and raise technical execution standards across teams

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 5+ years of equivalent software/AI engineering experience5+ years of experience in backend software engineering, APIs, and service integration2+ years of hands-on production experience with code-first agent frameworks (e.g., Lang Graph, Google ADK, AWS Strands, Claude Agent SDK, OpenAI Agents SDK, Pydantic AI)2+ years of experience building and deploying agentic solutions used in production environments, with a proven ability to debug and resolve production issues1+ years of experience designing, building, or integrating Model Context Protocol (MCP) servers, tools, skills, or plugins1+ years of experience implementing systematic evaluation harnesses or testing frameworks for LLM/agent behavior

Demonstrated experience using AI coding assistants (e.g., Claude Code, Codex, Copilot) as part of daily development workflows

Preferred Qualifications:

Hands-on experience with managed agent runtimes (Azure AI Foundry Agent Service, Vertex AI Agent Engine, Bedrock Agent Core) and containerized deployments (GKE, EKS, AKS)

Experience with retrieval and semantic search (embeddings, vector stores, RAG patterns, chunking, reranking with Postgres/pgvector, Azure AI Search, or Open Search) and evaluating retrieval efficacy

Experience with LLM evaluation tooling (Ragas, Deep Eval, Ranx, Braintrust, Lang Smith, Langfuse, promptfoo) integrated…