Production Ai Infrastructure Engineer
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As an Applied AI Engineer, you will build and operate AI runtime infrastructure for production agent workflows. You will implement tool calling, RAG, grounding, and context retrieval systems. You will also develop evaluation harnesses, golden datasets, quality benchmarks, and safety controls. The work supports practical AI features for mission-critical customer workflows.
Key Responsibilities
Build and operate AI runtime and orchestration infrastructureImplement RAG, grounding, and context-retrieval systemsDevelop evaluation harnesses, datasets, and quality benchmarksIntegrate testing, quality gates, and regression checksOwn production reliability, latency, cost, and failure managementRequirements:
Production experience shipping LLM
- or ML-powered softwareStrong understanding of systematic AI evaluation methodsAbility to manage cost and latency as constraintsClear communication with engineers, products, and customersPragmatic judgment focused on measurable customer valueApply applied AI engineering expertise across runtime architecture, RAG, evaluation, safety, and dependable production delivery.
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