Manager AI/ML Engineering
unitedhealthgroup
Job Description
- AI native Engineering & Delivery
- Drive the design, development, and rollout of AI/ML and Generative AI capabilities that solve business problems and improve operational outcomes
- Work closely with product, business, data, and architecture partners to define solution approaches and implementation strategies
- Ensure AI-enabled applications meet expectations for performance, scalability, maintainability, and regulatory compliance
- Promote adoption of reusable frameworks, accelerator assets, and engineering best practices to improve delivery efficiency
- Lead execution of engineering roadmaps, release plans, and solution enhancements across multiple initiatives
- ML Ops, Platform Engineering & Cloud Enablement
- Build and enhance enterprise ML Ops capabilities supporting the full AI lifecycle from experimentation through production operations
- Implement automated workflows for model training, validation, deployment, monitoring, rollback, and version management
- Establish model observability practices, including performance monitoring, drift detection, retraining strategies, and operational intelligence
- Improve reproducibility and governance of datasets, prompts, models, features, and experiments
- Partner with platform and infrastructure teams to advance CI/CD, Infrastructure-as-Code, containerization, and deployment automation
- Enable scalable and cost-efficient AI workloads across cloud platforms and modern engineering ecosystems
- Responsible AI & Technical Governance
- Develop and apply standards for responsible and trustworthy AI adoption
- Establish evaluation approaches for model quality, accuracy, explainability, safety, and risk management
- Guide implementation of retrieval, prompting, orchestration, and human oversight patterns for GenAI solutions
- Assess emerging technologies and identify opportunities that create measurable business value
- Contribute to architectural decisions, engineering standards, and technology modernization efforts
- Engineering Leadership & Business Partnership
- Lead and mentor teams of AI/ML engineers, fostering ownership, technical excellence, and continuous learning
- Support talent development through coaching, skill growth, succession planning, and knowledge-sharing initiatives
- Coordinate with cross-functional stakeholders to manage priorities, dependencies, risks, and resource needs
- Provide transparency into delivery progress, operational metrics, adoption trends, and business outcomes
- Influence AI adoption and engineering maturity within the broader organization through collaboration and thought leadership
- Demonstrate adherence to organizational policies, compliance requirements, security standards, and evolving business practices while maintaining a culture of accountability and integrity
- Design, develop, and deploy AI-powered solutions using no-code, low-code, and advanced platforms, translating business needs into scalable applications that enhance products, workflows, and decision-making
- Comply with all applicable Company policies, procedures, and business directives, changes including those relating to work location, team assignments, work schedules, and flexible work arrangements