Job Description & Details
This is a heavy-hitting architecture role where you will be designing and delivering enterprise-grade Agentic AI and GenAI solutions primarily within the Microsoft ecosystem. If you enjoy bridging the gap between high-level client strategy and hands-on multi-agent system design using tools like AutoGen, Semantic Kernel, and Azure OpenAI, this position puts you right in the center of the action.
What You'll Actually Be Doing
Expect to spend your days jumping between whiteboard architecture sessions with client stakeholders and diving deep into code to unblock complex RAG pipelines or multi-agent orchestration flows. You'll lead the full ML and GenAI lifecycle—from initial proof-of-concept to production deployment—while ensuring your systems are secure, compliant with regulations like GDPR and CCPA, and heavily backed by robust MLOps practices.
The Core Tech Stack
You need to eat, sleep, and breathe the Microsoft Azure AI stack, including Azure OpenAI, Microsoft Foundry, and Copilot Studio, alongside heavy experience with Python, PySpark, Databricks, and LangChain/LangGraph. They are looking for someone who doesn't just talk about RAG pipelines and vector databases, but has actually built them at scale, incorporating guardrails, LLMOps, and autonomous workflow orchestration.
Interview Expectations
Be ready for deep architectural grilling on how you handle state management and error recovery in complex multi-agent systems built with frameworks like AutoGen or Semantic Kernel. The interviewer is secretly looking to see if you can balance theoretical design purity with the messy reality of enterprise data governance, PII compliance, and production latency constraints.
Application Advice
Make sure your resume screams Microsoft Azure and GenAI implementation, specifically highlighting keywords like Microsoft Foundry, Agentic Framework, vector databases, and MLOps right at the top. Don't just list technologies; include bullet points that prove you've taken LLM applications from a local Jupyter notebook all the way to secure, production-ready enterprise deployments.