Senior Manager AI ML Engineering

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.

Role Summary

The Sr Manager AI/ML Engineering will lead the design, development, deployment, and scaling of enterprise AI/ML solutions that improve clinical outcomes, patient engagement, operational efficiency, and regulatory compliance. This role is responsible for driving AI platform strategy, MLOps excellence, and production-scale machine learning systems while leading engineering teams that deliver innovative healthcare solutions using structured and unstructured data.

Primary Responsibilities

• AI/ML Solution Delivery and Platform Leadership
• Lead the design, development, deployment, and operationalization of AI-enabled products and machine learning models for clinical and healthcare applications
• Define and execute AI platform, model deployment, and engineering strategies that support enterprise-scale adoption of AI capabilities
• Design scalable, production-grade AI/ML architectures and systems that deliver reliable, real-time business insights
• MLOps and Engineering Excellence
• Establish and drive MLOps standards, automation practices, governance controls, and production monitoring to ensure model reliability, performance, and compliance
• Own model orchestration, data pipelines, and machine learning workflows, enabling efficient training, deployment, monitoring, and retraining processes
• Improve platform efficiency, resilience, and scalability through automation, testing, and continuous integration/deployment practices
• AI Innovation and Advanced Analytics
• Apply advanced AI/ML techniques including NLP, deep learning, semantic understanding, predictive modeling, computer vision, speech technologies, and related capabilities to solve complex healthcare challenges
• Leverage modern cloud, data, and distributed computing platforms to optimize clinical workflows, documentation, and decision support systems
• Leadership and Cross-Functional Collaboration
• Lead and mentor AI/ML engineering teams while fostering technical excellence and innovation
• Partner with product, architecture, data science, operations, and business stakeholders to prioritize initiatives, define milestones, and deliver strategic outcomes
• Communicate technical strategy, model performance, risks, and business value to senior leadership and stakeholders while influencing AI adoption across the organization
• 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
  

• Bachelor's degree in Computer Science, Engineering, Data Science, or a related quantitative field
• 5+ years of software engineering experience with demonstrated expertise across the Software Development Life Cycle (SDLC)
• Hands-on experience building and deploying machine learning solutions using Python, SQL, and/or PySpark
• Experience developing and supporting cloud-based AI/ML solutions in Azure, AWS, or Google Cloud Platform
• Solid understanding of CI/CD practices, automation frameworks, and production software delivery
  
  

• Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related quantitative discipline
• Experience with enterprise AI/ML platforms and technologies such as Databricks, Azure Machine Learning, Snowflake, or comparable solutions
• Experience building and scaling healthcare-focused AI solutions in regulated environments
• Deep expertise in MLOps practices including model monitoring, drift detection, automated retraining, and model lifecycle management