AI Agent Engineer

Role Overview

We are seeking an experienced AI Agent Engineer (Manufacturing AI — LangChain / LangGraph / RAG) to design, build, and ship production-grade agentic AI systems specifically for manufacturing clients.

Your Impact:

• Act as the technical lead on engagements delivering measurable operational wins: improving OEE, reducing downtime/scrap, enhancing quality accuracy, and speeding up response times.
• Create reusable AI capabilities that accelerate future deployments.

Key Responsibilities

Discovery & Roadmap: Assess current operations, data maturity, and AI readiness to identify high-ROI use cases. Deliver prioritized 90-day roadmaps balancing quick wins with structural builds.

Agentic AI Development: Build production systems using LangChain and LangGraph. Design robust tool calling mechanisms, MCP integrations, and guardrails against hallucinations. Stand up RAG pipelines over manufacturing knowledge (SOPs, work orders, manuals) equipped with proper evaluation harnesses.

System Integration: Seamlessly integrate agents with MES, ERP, CMMS, and data platforms like Snowflake or Databricks. Leverage Azure/AWS/GCP ecosystems using APIs, webhooks, and automation tools (Workato, n8n, Power Automate). Handle governance responsibly.

Testing & Go-Live: Define success criteria, lead UAT, monitor latency/accuracy in production, and troubleshoot live systems.

Enablement & Reusable IP: Document architectures and runbooks for async global collaboration. Contribute templates and accelerators to the internal library.

Stakeholder Partnership: Partner with plant leaders and CIO/CDO teams to translate operational needs into technical plans. Advise honestly on AI automation potential without overpromising.

Required Skills

• Core Tech: Expert proficiency in LangChain, LangGraph, MCP (Model Context Protocol), Python, and production RAG systems.
  
• Tech Stack: Strong experience with Cloud platforms (Azure/AWS/GCP) and Data lakes (Snowflake/Databricks).
  
• Automation: Hands-on integration using Workato, n8n, Power Automate, MuleSoft, or Boomi.
  
• Domain Knowledge: Familiarity with Smart Factory/Industry 4.0 concepts, OT/IT convergence, and manufacturing operations (MES, ERP).
  

Preferred Experience

• 5+ years in software/AI engineering focused on agentic or LLM systems.
  
• Experience in discrete/process manufacturing or regulated domains.
  
• Computer vision exposure for visual inspection/defect detection (Plus).
  
• Certifications: AWS ML, Azure AI Engineer, NVIDIA, ISA CAP, etc.

  What Success Looks Like

  • Premium production AI systems adopted by operations teams (no stalled pilots).
  • Measurable improvement in real metrics like OEE or quality accuracy.
  • High client trust and strong cross-pod collaboration.