Agentic AI Engineer

Title: Senior Agentic AI Engineer (Hybrid - San Francisco)

Location: San Francisco, CA

Position Type: Full-Time

About the Role

A high-growth enterprise AI platform is seeking a Senior Agentic AI Engineer to drive the development of autonomous AI agents and digital twin infrastructure for advanced manufacturing and complex physical systems. You will own the core agent harness and evaluation infrastructure that powers autonomous decision-making, designing trustworthy, stateful AI applications that translate complex technical data into high-impact operational decisions.

Key Responsibilities

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  Architect and build production-grade agent orchestration layers and stateful multi-agent workflows leveraging or extending frameworks like LangGraph, Google ADK, or OpenAI Agents SDK.

  
  


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  Develop MCP servers and tool-registration APIs to give agents persistent context and shared state across complex enterprise workflows.

  
  


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  Construct human-in-the-loop systems, including review tooling, checkpoints, and judge-gated flows to ensure system output accuracy and reliability.

  
  


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  Build first-class evaluation infrastructure using LLM-as-judge gating, golden datasets, replay runs, and full-stack tracing.

  
  


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  Implement knowledge-graph-backed agent context (Neo4j) and specialized retrieval-augmented generation (RAG) pipelines for complex domain retrieval.

  
  


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  Partner with security leads to ensure proper RBAC, audit trails, and network-isolated serving for enterprise customer environments.

  
  

Required Qualifications

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  5+ years of production software engineering experience, including 2+ years shipping and operating LLM or agentic systems in live environments.

  
  


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  Deep architectural knowledge of stateful agent orchestration frameworks, including execution models, state management, tool orchestration, and failure handling.

  
  


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  Demonstrated experience building evaluation infrastructure (judge thresholds, golden-set regressions, replay runs) and end-to-end RAG architectures.

  
  


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  Hands-on proficiency with Docker, Kubernetes, and major cloud infrastructure (Azure, AWS, or Google Cloud Platform).

  
  


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  Track record of taking complex, stateful systems from design into highly observable production deployment.

  
  

Preferred Qualifications

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  Experience with programmatic prompt optimization (DSPy or similar) and graph databases (Neo4j) in production.

  
  


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  Background in uncertainty quantification, model calibration, or network-isolated/air-gapped enterprise deployments.

  
  


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  Exposure to complex engineering domains, hardware systems, or advanced manufacturing operations.

  
  

If you think you would be a good fit from this role, we'd like to hear from you!

Oscar Associates Limited (US) is acting as an Employment Agency in relation to this vacancy.