Applied AI Engineer

**Must\-Have Requirements** **Requirement Details** 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, TypeScript, 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 **\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_** **Preferred / Differentiators** * Built multi\-step agentic workflows with tool use and function calling * Experience with agent orchestration frameworks (LangGraph, CrewAI, Claude Agent SDK, Google ADK, OpenAI ADK) * Built guardrails, fallbacks, or graceful degradation for AI systems * Streaming inference and async agent orchestration * Cost/latency optimization: caching, batching, prompt compression * ML observability tools: Langfuse, Arize, Braintrust, W\&B * Retrieval systems (vector search, hybrid search) — as a tool, not the focus **Location**: Austin, TX **Salary Range**:$70,000\-$130,000 Per a Year \#LI\-AS3 Location Austin, TX Job Function TECHNOLOGY Role Engineer Job Id 4