Job Description & Details
This is a heavy-duty AI engineering contract focused on enterprise-grade integrations using Microsoft's modern AI ecosystem. If you enjoy bridging the gap between raw LLM capabilities and practical business workflows via tools like Copilot Studio and Azure AI Foundry, this role will keep you challenged.
What You'll Actually Be Doing
You will be knee-deep in building, deploying, and orchestrating intelligent agents and automation solutions that actually function in a production environment. Expect to spend your days wiring up RAG pipelines, configuring vector databases, and integrating generative AI with platforms like Power Automate, Dataverse, and MuleSoft. The real challenge here isn't just writing the initial prompt, but ensuring agent interoperability, managing tool orchestration, and handling AI security and compliance at an enterprise scale.
The Core Tech Stack
You need solid Python fundamentals paired with deep, hands-on experience in the Microsoft Azure AI stack, specifically Azure AI Foundry, Azure OpenAI, and Azure AI Search. Frameworks like LangChain and LangGraph are non-negotiable for handling orchestration, and you must know your way around Copilot Studio and the Azure AI Foundry Agent Service. Familiarity with API management layers like MuleSoft or Azure APIM will make or break your ability to deliver seamless integrations here.
Interview Expectations
Expect the hiring team to test your real-world architectural knowledge by asking how you handle hallucination reduction and context window limits in a complex RAG pipeline using Azure AI Search. They want to see that you understand the nuances of token management, vector embeddings, and knowledge grounding, rather than just knowing how to call an API. Another likely discussion point will revolve around agent interoperability and security—be prepared to explain how you implement guardrails and monitor AI FinOps when deploying agents into production.
Application Advice
Skip the generic AI buzzwords and make sure your resume immediately highlights your production-level deployments using Azure AI services and Python. Explicitly list out your experience with LangChain, LangGraph, and Copilot Studio so the ATS flags you right away. If you have built custom connectors or integrated LLMs with Power Platform or MuleSoft, bring those projects to the very top of your experience section to prove you can handle the enterprise workflow requirements of this hybrid role.