fairlife
AI Automation Engineer
About this role
fairlife seeks an AI Automation Engineer to design and deploy intelligent agents that automate complex business workflows across manufacturing, supply chain, and operations. You'll build production-grade agentic systems using modern AI frameworks and Microsoft Fabric/Azure to transform manual processes into reliable, autonomous automation.
What you'll do
- Design and deploy AI agents that autonomously reason, plan, and execute multi-step tasks to automate business workflows
- Identify manual and repetitive processes and re-engineer them as reliable automated agentic workflows
- Orchestrate single and multi-agent workflows using frameworks like LangChain, LangGraph, CrewAI, or AutoGen
- Integrate agents with internal tools, APIs, databases, and enterprise systems via Model Context Protocol and other methods
- Implement retrieval-augmented generation (RAG) pipelines to ground agents in domain-specific data
- Deploy, monitor, and continuously improve agentic systems in production using MLOps/LLMOps best practices
What they're looking for
- Python programming
- Large language models (LLMs) and foundation models
- Agentic AI frameworks (LangChain, LangGraph, CrewAI, AutoGen)
- Prompt engineering and function calling
- Retrieval-augmented generation (RAG)
- Microsoft Fabric and Azure
- MLOps/LLMOps practices
- API integration and enterprise system connectivity
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fairlife
fairlife manufactures dairy products and operates processing facilities that require sophisticated automation and operational optimization. The company is hiring engineers across environmental health & safety systems, process automation, warehouse automation, and production efficiency to enhance manufacturing reliability, reduce waste, and ensure regulatory compliance.
- Website
- fairlife.com
Likely interview questions
- Walk us through a project where you built and deployed an AI agent or multi-agent system—what frameworks did you use and what challenges did you overcome?
- How would you approach integrating an AI agent with multiple internal systems and APIs to ensure reliable end-to-end task execution?