Join Optum, a global leader dedicated to improving health outcomes through innovative technology. We are seeking a Manager in AI/ML Engineering to drive the development and deployment of cutting-edge AI solutions for Digital Analytics. This role offers a dynamic environment where you can leverage your expertise to connect people with the care they need and advance health optimization on a global scale.

Our culture thrives on inclusion, collaboration with talented peers, and provides comprehensive benefits and career development opportunities. Be a part of a team that is Caring, Connecting, and Growing together, making a tangible impact on the communities we serve.

Spearhead the development and execution of AI/ML, Generative AI, and Agentic AI solutions within Digital Analytics to enhance measurement, insights, experimentation, and optimization across enterprise web and mobile experiences.

Integrate AI across the Digital Analytics lifecycle, from requirements gathering and technical specifications to implementation, QA, reporting, and optimization. Develop AI-enabled capabilities seamlessly integrated with the Adobe Analytics ecosystem.

Collaborate with Product, Digital Analytics, Data Engineering, UX, Marketing, and Technology teams to identify high-value AI/ML opportunities and translate business challenges into scalable technical solutions. Design and engineer GenAI, RAG, Agentic AI, and intelligent automation solutions using LLMs, vector databases, and enterprise knowledge sources.

Provide hands-on technical leadership in architecture, prototyping, engineering, and productionizing AI solutions, while continuously evaluating emerging AI models and frameworks. Apply Agile, DevSecOps, MLOps, and AIDLC practices for secure, governed, and automated deployment and monitoring.

A Master's degree in Computer Science, Engineering, Mathematics, Statistics, Data Science, or a related technical field is required.

Possess a minimum of 8 years of experience in Software Engineering, Data Science, Analytics, or AI/ML Engineering, with at least 3 years specifically focused on Generative AI and modern AI engineering practices.

Demonstrated hands-on experience with OpenAI-compatible LLMs, Claude, Gemini, LangChain/LangGraph, AI Agents, RAG, Vector Databases, Prompt Engineering, and model fine-tuning is essential. Proficiency with modern data and cloud platforms like Databricks, Azure, AWS, or GCP is expected.

Strong understanding of Digital Analytics, customer journey data, and familiarity with platforms such as Adobe Analytics, CJA, AEP/WebSDK, Adobe Launch, or Adobe Target is highly preferred. Solid knowledge of Python, APIs, data pipelines, model orchestration, MLflow, TensorFlow, PyTorch, Scikit-learn, and production AI engineering is critical. A firm grasp of AI governance, security, observability, model evaluation, and responsible AI practices is also necessary.