Applied AI Senior EngineerLocation: Sunnyvale, CA/Austin, TX (Onsite)FulltimeMust-Have RequirementsBackend/Systems Experience3+ years building production backend or distributed systems (pre-AI experience required)Production AI SystemsHas shipped AI/LLM features serving real users at scale — not just prototypes or demosAgentic SystemsHas built AI agents, skills, tools, or MCP (Model Context Protocol) integrationsPythonProficient for backend developmentSecondary LanguageWorking knowledge of Go, TypeScript, or RustCloud InfrastructureDeep experience with AWS/GCP/Azure — cost optimization, compute decisions, not just deploymentContainer & OrchestrationHands-on with Docker and Kubernetes — can build, deploy, debug, and scale services themselvesLLM IntegrationUnderstands token economics, context limits, rate limiting, structured outputs, API failure modesLLM EvaluationUnderstands how to evaluate LLM outputs and the inherent challenges (non-determinism, quality measurement, regression detection)Hands-On EngineerNot just an architect — writes code, debugs production issues, deploys their own workPreferred / DifferentiatorsBuilt multi-step agentic workflows with tool use and function callingExperience with agent orchestration frameworks (LangGraph, CrewAI, Claude Agent SDK, Google ADK, OpenAI ADK)Built guardrails, fallbacks, or graceful degradation for AI systemsStreaming inference and async agent orchestrationCost/latency optimization: caching, batching, prompt compressionML observability tools: Langfuse, Arize, Braintrust, W&BRetrieval systems (vector search, hybrid search) — as a tool, not the focus