Lead AI/ML Engineer

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.    

We are seeking a Sr Manager, AI Systems Engineering to lead the design, delivery, and operation of enterprise AI platforms and production AI systems. This role is is responsible for driving platform strategy, engineering excellence, AI operationalization, and scalable delivery across multiple AI initiatives.

The ideal candidate combines deep expertise in AI systems, distributed architectures, cloud platforms, MLOps/LLMOps, and AI infrastructure with the leadership ability to build engineering capabilities, establish operating standards, and accelerate enterprise AI adoption.

Success will be measured through platform reliability, delivery outcomes, AI operational maturity, engineering productivity, reusability, and enterprise adoption of AI capabilities.

Primary Responsibilities:

• AI/ML Engineering & Solution Enablement
  • Provide technical leadership for enterprise AI/ML, Generative AI, and Agentic AI solution delivery
  • Partner with Applied Scientists and AI Engineers to operationalize machine learning models and AI innovations at scale
  • Guide architecture and deployment strategies for:
    • Machine Learning and Deep Learning models
    • Generative AI applications
    • Retrieval-Augmented Generation (RAG) solutions
    • Agentic AI systems
    • Intelligent automation platforms
  • Establish reusable patterns for model serving feature engineering, inference pipelines, evaluation frameworks, and AI workflow orchestration
  • Drive the adoption of engineering best practices across the AI lifecycle including experimentation, deployment, monitoring, governance, and continuous improvement
  • Evaluate emerging AI technologies, frameworks, and foundation models to improve delivery velocity and enterprise AI capabilities
  • Ensure AI solutions are designed for scalability, reliability, explainability, operational readiness, and measurable business impact
• AI Systems & Platform Strategy
  • Define strategy and roadmap for enterprise AI platforms, AI infrastructure, and operational AI services
  • Drive architecture decisions supporting AI/ML, Generative AI, Agentic AI, and intelligent automation workloads
  • Establish reference architectures, platform standards, reusable services, and engineering blueprints
  • Partner with AI, Data, Product, Security, and Enterprise Architecture teams to align platform investments with business priorities
• AI Platform Delivery & Operationalization
  • Lead delivery of enterprise AI platforms supporting model development, deployment, serving, orchestration, governance, and lifecycle management
  • Drive platform adoption by enabling self-service deployment and standardized AI engineering practices
  • Establish reusable deployment patterns, SDKs, APIs, accelerators, and shared platform services
  • Ensure AI platforms support scalability, reliability, security, and operational efficiency requirements
• AI Runtime, MLOps & Agentic-Ops Leadership
  • Define enterprise standards for MLOps, LLMOps, and AgentOps
  • Drive automation across:
  • Model lifecycle management
  • Deployment workflows
  • Environment provisioning
  • Monitoring and governance
  • Release management
  • Establish operational frameworks for LLMs, RAG systems, AI agents, and multi-agent ecosystems
  • Improve delivery of velocity through automation, platform engineering, and reusable workflows
• AI Systems Engineering
  • Lead engineering of high-performance AI systems and distributed services
  • Define patterns for model serving inference orchestration, workflow execution, event-driven processing, and workload management
  • Establish architectures supporting real-time, asynchronous, and batch AI workloads
  • Drive optimization of throughput, latency, resilience, scalability, and cost efficiency
• Reliability, Observability & Governance
  • Define enterprise observability standards for AI platforms and AI applications
  • Establish monitoring frameworks covering:
  • Platform health
  • Model performance
  • Agent effectiveness
  • Prompt behavior
  • Operational KPIs
  • Drive SRE practices, operational readiness, incident management, and reliability improvements
  • Ensure adherence to Responsible AI, governance, security, compliance, and risk management requirements
• Engineering Leadership & Organizational Impact
  • Lead and mentor AI Systems Engineers and Platform Engineers across multiple initiatives
  • Establish engineering standards, review processes, operational procedures, and architecture governance
  • Develop organizational capability in AI platform engineering, automation, and AI operations
  • Drive technology modernization and continuous improvement initiatives
  • Influence enterprise AI engineering strategy, platform direction, and investment priorities
• 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 regards 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

Required Qualifications:

• Bachelor's degree in computer science, Engineering, Artificial Intelligence, Data Science, or related field
• 15+ years of experience in software engineering, platform engineering, AI systems engineering, or distributed systems development
• 5+ years of leading engineering teams, platform initiatives, or large-scale technology programs
• Proven experience building and operating enterprise AI platforms and production AI systems
• Solid experience with MLOps, LLMOps, deployment automation, and AI lifecycle management.
• Experience building APIs, microservices, event-driven systems, and platform services
• Experience working with Azure, AWS, and/or GCP environments
• Proficiency in Python and modern backend engineering frameworks.
• Proven solid leadership, delivery management, stakeholder engagement, and problem-solving skills
• Proven solid expertise in:
  • Distributed systems
  • Backend engineering
  • AI infrastructure
  • Cloud-native architectures
  • Platform engineering
  • Experience operationalizing:
  • Machine Learning workloads
  • Generative AI applications
  • RAG architectures
  • Agentic AI systems

Preferred Qualifications:

• Master's Degree
• Experience leading enterprise AI platform engineering teams
• Experience defining AI operating models, platform governance, and shared service strategies
• Expertise with MLflow, Kubeflow, Azure ML, SageMaker, Vertex AI, Databricks, or equivalent platforms
• Experience with LangChain, LangGraph, Semantic Kernel, AutoGen, CrewAI, LlamaIndex, or similar AI orchestration frameworks
• Experience deploying and managing foundation models and enterprise GenAI ecosystems
• Experience with Kafka, Spark, Redis, Elasticsearch, Databricks, and large-scale distributed platforms
• Experience implementing AI observability, evaluation frameworks, agent monitoring, and operational governance
• Experience driving reusable platform capabilities, engineering frameworks, and enterprise accelerators
• Healthcare, financial services, insurance, or other regulated industry experience
• Proven expertise in vector search, semantic retrieval, knowledge systems, and RAG architectures
• Proven contributions to enterprise platforms, patents, publications, innovation programs, or open-source communities

Technical Skills

• AI Platforms & Systems: AI Platforms, Model Serving, Inference Orchestration, AI Infrastructure, Distributed AI Systems, Intelligent Automation
• Generative AI & Agentic AI: LLMs, RAG, Embeddings, Vector Databases, Semantic Retrieval, Agentic AI, Multi-Agent Systems
• AI Operations: MLOps, LLMOps, AgentOps, Deployment Automation, Model Lifecycle Management, Governance
• AI/ML & Applied AI: Machine Learning, Deep Learning, Predictive Analytics, NLP, Recommendation Systems, Time-Series Forecasting, Model Evaluation, Feature Engineering, AI Solution Architecture
• Generative AI & Agentic AI: LLMs, RAG, Prompt Engineering, Semantic Retrieval, Vector Databases, AI Agents, Multi-Agent Systems, Workflow Orchestration, Intelligent Automation
• Backend & Platform Engineering: Python, APIs, Microservices, Event-Driven Architecture, Distributed Systems, Service Platforms
• Cloud & Infrastructure: Azure, AWS, GCP, Kubernetes, Docker, Infrastructure Automation
• Data & Processing Platforms: Kafka, Spark, Databricks, Redis, Elasticsearch, Real-Time Processing
• Reliability & Governance: Observability, Monitoring, SRE, Responsible AI, Security, Compliance, Risk Management
• Leadership: Platform Strategy, Engineering Management, Architecture Governance, Delivery Leadership, Stakeholder Management

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.