Applied AI Engineer

• Backend/Systems Experience 3+ years building production backend or distributed systems (pre-AI experience required)
• Production AI Systems Has shipped AI/LLM features serving real users at scale — not just prototypes or demos
• Agentic Systems Has built AI agents, skills, tools, or MCP (Model Context Protocol) integrations
• Python Proficient for backend development
• Secondary Language Working knowledge of Go, Type Script, or Rust
• Cloud Infrastructure Deep experience with AWS/GCP/Azure — cost optimization, compute decisions, not just deployment
• Container & Orchestration Hands-on with Docker and Kubernetes — can build, deploy, debug, and scale services themselves
• LLM Integration Understands token economics, context limits, rate limiting, structured outputs, API failure modes
• LLM Evaluation Understands how to evaluate LLM outputs and the inherent challenges (non-determinism, quality measurement, regression detection)
• Hands-On Engineer Not just an architect — writes code, debugs production issues, deploys their own work

Skills:

AI Agents, MCP Integration, Go, Type Script, or Rust, AWS/GCP,Docker, Kubernetes, Lang Graph, Retrieval systems (vector search, hybrid search)