Join Optum's global organization as an Associate AI/ML Engineer and help shape the future of healthcare through innovative technology. This role offers a chance to significantly improve health outcomes by connecting individuals with essential care, pharmacy benefits, data, and resources. You'll be part of an inclusive culture, working alongside talented colleagues and accessing comprehensive benefits and career development opportunities. Make a tangible impact as we advance health optimization worldwide, embodying our values of Caring, Connecting, and Growing together.

In this pivotal role, you will engineer advanced AI and machine learning solutions to transform healthcare delivery. Your contributions will focus on designing, developing, and implementing generative AI, retrieval-augmented generation (RAG) systems, and agentic workflows to address complex business and clinical issues.

Key responsibilities include: - Designing and implementing AI systems for conversational search. - Developing AI/ML data ingestion quality gates. - Evaluating, debugging, and refining conversational AI for accuracy. - Monitoring and optimizing system performance for latency and cost. - Exploring reinforcement learning and self-improving techniques. - Collaborating with cross-functional teams on scalable solutions. - Ensuring responsible and ethical AI practices throughout development. - Building and deploying production-grade AI applications, including RAG and agentic workflows. - Developing and maintaining scalable data pipelines using Spark, Scala, and Python. - Integrating event-streaming technologies like Kafka for real-time data processing. - Exposing AI model outputs via secure REST APIs for business platforms. - Applying security best practices and data privacy standards.

We are seeking candidates with a solid foundation in software engineering and a passion for AI/ML. A minimum of 3 years of hands-on experience is required, specifically in building AI/GenAI or LLM-based applications such as RAG systems, agentic workflows, or AI chatbots.

Essential qualifications include: - Experience designing and building batch and real-time streaming data pipelines with Spark, Scala, or Python. - Hands-on experience with event-streaming platforms like Apache Kafka or Azure Event Hubs. - Proven ability to build data pipelines within cloud environments such as Azure Databricks or Snowflake. - Practical experience integrating foundation models via commercial or open-source APIs. - Proficiency with at least one GenAI orchestration framework (e.g., LangChain, LangGraph). - A deep understanding of RAG components and agentic patterns. - Solid knowledge of REST APIs, microservices, Git, CI/CD, and Docker. - Awareness of security, privacy, and responsible AI practices is crucial for production systems.