Staff AI Engineer

What you'll do

• Design, build, test, deploy, and operate end-to-end full-stack software; contribute to architecture, platform enablement, code reviews, and engineering standards.
• Develop custom AI agents and MCP-integrated systems for workflow automation, decision support, and interoperability.
• Integrate AI services and RAG, and ensure production systems meet reliability, security, performance, and observability needs.

What they ask for

• Strong full-stack engineering fundamentals and production-grade backend or full-stack systems experience, including API design, service integration, and data persistence.
• Experience with cloud-native environments, CI/CD, containerized deployments, and modern operational practices.
• Experience with C#, ASP.NET, Angular, RESTful APIs, SQL and NoSQL databases, and Kubernetes-based platforms.
• Experience building custom AI agents, integrating MCP or equivalent interfaces, and implementing RAG-based systems; knowledge of prompt engineering and AI guardrails.

Nice to have

• Experience using AI-enabled development practices and evaluating AI-generated output for production systems.
• Experience designing and operating distributed systems on Kubernetes, including message-driven architectures, scaling, and fault tolerance.

Tools

C#, ASP.NET, Angular, RESTful APIs, SQL, NoSQL, Kubernetes, Model Context Protocol (MCP)

AI focus

Build custom agents and MCP-integrated applications; use AI-assisted development, LLMs, embeddings, search, and RAG to automate workflows and deliver reliable production AI systems.