Join Optum, a global healthcare technology leader, in advancing health optimization worldwide. We are dedicated to improving lives by connecting people with the care, resources, and data they need to thrive. Our inclusive culture, supportive team, and extensive development opportunities foster growth and impact. Come make a difference in the communities we serve as we innovate and expand healthcare solutions on a global scale. Embrace a culture of Caring, Connecting, and Growing together.

This role is key to driving innovation in AI/ML engineering, focusing on Generative AI, RAG, and MLOps to solve complex business challenges and enhance operational efficiency. You will collaborate with diverse teams to architect and implement cutting-edge AI solutions that meet rigorous standards for performance, scalability, and compliance.

Lead the design, development, and deployment of AI/ML and Generative AI capabilities. Collaborate with product, business, and architecture partners to define and execute solution strategies. Ensure AI applications are performant, scalable, and compliant.

Drive the advancement of enterprise MLOps, supporting the entire AI lifecycle from experimentation to production. Implement automated workflows for model training, deployment, monitoring, and governance. Establish robust model observability practices, including performance monitoring and drift detection.

Develop and enforce standards for responsible and trustworthy AI, including quality, accuracy, explainability, and risk management. Guide the implementation of GenAI patterns like retrieval, prompting, and human oversight. Assess emerging technologies and identify opportunities for business value creation. Contribute to architectural decisions and engineering standards.

Lead and mentor AI/ML engineering teams, fostering technical excellence and continuous learning. Support talent development through coaching and knowledge sharing. Coordinate with cross-functional stakeholders to manage priorities, risks, and resources. Influence AI adoption and engineering maturity across the organization. Maintain adherence to policies, security standards, and business practices with accountability and integrity.

A Bachelor's degree in Computer Science, AI, Data Science, Engineering, Mathematics, or a related field is required, though equivalent experience will be considered.

Possess hands-on experience in AI/ML engineering, software engineering, or data engineering, with a strong track record in delivering Generative AI, LLM, AI Agent, Copilot, or intelligent automation solutions. Experience with prompt engineering, workflow orchestration, and AI solution evaluation is essential.

Demonstrate proficiency in integrating AI solutions with cloud platforms, APIs, databases, and enterprise applications, along with experience in cloud-native development. Familiarity with RAG architectures, embeddings, vector databases, and semantic search is crucial.

Solid understanding of MLOps practices, including model deployment, versioning, monitoring, and lifecycle management. Knowledge of software engineering best practices such as source control, automated testing, CI/CD, and release management is expected.

Familiarity with responsible AI principles, security, governance, and operational controls for AI solutions. Strong programming skills in Python, including API and service development, are necessary, alongside excellent troubleshooting, problem-solving, communication, and stakeholder management abilities.