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Job Description
Structured overview of role & requirementsAbout This Role
Design, build, and productionize autonomous multi-agent AI systems using frameworks like LangGraph, AutoGen, or Semantic Kernel on Microsoft Azure.
Lead architecture, LLMOps/MLOps, and evaluation for GenAI initiatives, including RAG pipelines, agent safety, and integration with enterprise APIs.
Mentor junior data scientists, lead reviews, and drive technical direction for agentic AI platform development.
Minimum Requirements
8-10 years of professional experience in data science/ML with at least 3 years in production-level LLM or GenAI application development.
Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Mathematics, or related field.
Hands-on experience with agentic AI frameworks (e.g., LangChain, LangGraph, AutoGen, CrewAI, Semantic Kernel) and Azure cloud services including Azure OpenAI, Azure ML, Databricks, and Azure AI Search.
Strong Python programming skills (including async programming and API development), deep understanding of LLM application patterns, MLOps/LLMOps experience, and SQL proficiency.
Ideal Candidate Profile
Experienced in architecting complex agentic AI solutions end-to-end, combining classical ML and LLM-based workflows on Microsoft Azure platform.
Demonstrates technical leadership with proven ability to mentor teams, conduct code/design reviews, and drive adoption of engineering best practices.
Comfortable with operationalizing LLM safety guardrails, evaluation frameworks, and integrating large-scale data pipelines across enterprise systems.