Join Optum, a global leader dedicated to improving health outcomes through innovative technology. We empower millions to live healthier lives by connecting them with essential care, pharmacy benefits, and data resources.

Our inclusive culture fosters collaboration with talented peers and provides comprehensive benefits and career development. Make a significant impact by advancing health optimization worldwide. We invite you to begin Caring, Connecting, and Growing with us.

Spearhead the design and development of AI-driven, cloud-native applications, intelligent automation workflows, and AI agents using Python, SQL databases (PostgreSQL, MongoDB, Oracle), and leading cloud platforms (Azure, GCP, AWS).

Build, integrate, test, and deploy cutting-edge GenAI, Agentic AI, LLM, and RAG-based solutions tailored for enterprise needs.

Establish and maintain robust automation frameworks, validation engines, data extraction capabilities, and autonomous remediation workflows to minimize manual effort and enhance operational accuracy.

Collaborate effectively with business stakeholders, architects, product owners, and engineering teams to translate requirements into scalable, secure, and production-ready technical solutions.

Uphold high standards for code quality, CI/CD readiness, comprehensive testing, thorough documentation, vigilant monitoring, and adherence to enterprise engineering and AI governance guidelines.

A graduate degree or equivalent professional experience is essential.

Over 10 years of comprehensive professional experience in software engineering, cloud application development, automation, or AI solution delivery is required.

Possess at least 5 years of hands-on expertise across .NET, Python, SQL, application development, and enterprise solution implementation.

Demonstrate 4+ years of practical experience delivering AI, Agentic AI, LLM-based, GenAI, or RAG-based projects in production or enterprise environments.

Showcase solid experience with Azure and/or GCP cloud platforms, including cloud-native design, deployment, integration, and operational support.

Proficiency with AI productivity and engineering tools such as GitHub Copilot, Microsoft 365 Copilot, Codex, Claude, and VS Code AI-assisted development is expected.

Possess hands-on knowledge of LLM-based frameworks, Agentic frameworks (e.g., LangGraph, LangChain, CrewAI), and familiarity with MCP-based patterns.

A strong understanding of RAG patterns, embeddings, vector databases, semantic search, Azure AI Search, ChromaDB, MongoDB, cognitive services, NLP, and knowledge retrieval capabilities is crucial.

Solid engineering fundamentals are a must, encompassing APIs, microservices, scalable system design, testing, debugging, documentation, and secure development practices.