DevOps + AI Engineer

Job Summary
We are seeking a Software Engineer to build and deploy AI-enabled applications in partnership with AI Engineers and product teams. This role focuses on application architecture project scaffolding enterprise integration cloud implementation and deployment readiness needed to move AI use cases from PoC to MVP and production.

The ideal candidate brings strong software engineering and cloud delivery experience with practical exposure to AI solutions and common AI architecture patterns. This person does not need deep AI model-development expertise but should understand how AI applications are structured collaborate effectively with AI Engineers and be adept at using modern AI productivity tools such as GitHub Copilot Claude Code and similar tools in a disciplined way to accelerate engineering delivery.

Key Responsibilities
Integrate AI solutions with UAIS and other UHG/Optum systems to enable secure enterprise deployment.
Select and apply the right technical patterns for AI solutions in partnership with AI Engineers.
Scaffold projects repositories pipelines environments and shared services needed for delivery.
Build core application components APIs data integrations and deployment-ready services.
Partner closely with DevOps and platform teams to ensure secure scalable and supportable deployments.
Contribute to CI/CD testing release processes and operational readiness for MVP and production solutions.

Key Skills & Experience
Strong software engineering fundamentals with a hands-on builder mindset and experience delivering production-grade applications.
Practical experience working on AI solutions alongside AI Engineers with understanding of common patterns such as RAG agentic workflows API-based model integration and evaluation or observability needs.
Strong Azure experience across infrastructure platform services security identity and networking.
Experience with DevOps tooling CI/CD pipelines environment management and secure deployment practices.
Strong experience with open source and cloud technologies such as Neo4j Cosmos DB PostgreSQL MongoDB Kafka Containers K8s FastAPI and related application frameworks.
Strong understanding of data platform choices including when to use relational NoSQL graph vector and event-driven architectural patterns.