Agentic AI Architect with Azure Databricks

Experience: 16 20 years; ideal profile has 15+ years in Data & Analytics.

Location: Chicago, IL - Hybrid, 3 days/week in office.

Core requirement: Strong Azure + Databricks + Data Engineering + Agentic AI experience.

Data Platform: Azure Databricks, Delta Lake, Unity Catalog, ADLS Gen2, ADF, Databricks Workflows/DLT.

Data Engineering: PySpark, Spark SQL, Python, SQL, ETL/ELT modernization.

Agentic AI: AI Agents for ingestion, mapping, schema evolution, data quality, pipeline optimization, RCA, governance, and self-healing.

GenAI: Azure OpenAI, RAG, LangChain, LangGraph, Semantic Kernel, AutoGen, MCP, Vector DBs.

AI-DLC: AI-assisted requirements, data modeling, code/pipeline generation, testing, code review, documentation, deployment, and monitoring.

Governance: Responsible AI, guardrails, security, auditability, observability, cost monitoring, explainability, and HITL.

DevOps/MLOps: Azure DevOps, GitHub Actions, CI/CD, MLOps, LLMOps, AI evaluation/testing.

Leadership: Enterprise architecture, reusable AI agents/accelerators, mentoring teams, and CXO-level AI strategy/ROI discussions.

Certifications: Databricks, Azure Solution Architect/Data Engineer, Azure OpenAI, GenAI/Agentic AI certifications are preferred.

Education: BE/ME/BTech/MTech/BSc/MSc or equivalent engineering/science degree.

Key success expectation: Drive 30 50% improvement in Data Engineering productivity through Agentic AI.