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Applied AI Engineer

Job

Talent Groups

Austin, TX (In Person)

Full-Time

Posted 3 days ago (Updated 22 hours ago) • Actively hiring

Expires 6/7/2026

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Job Description

Must-Have Requirements 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/Google Cloud Platform/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

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