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# Azure Databricks & Agentic AI Architect

- **Company:** Algo Soft Solutions LLC
- **Location:** United States (Remote available)
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Artificial Intelligence, Data Analysis, Microsoft Azure, Code Generation, Continuous Integration, Data Architecture, Information Engineering, Database Development, Graph Database, Apache Hive, Python (Programming Language), OpenAI, Azure Data Lake, Enterprise Data Management, Data Ingestion, LangChain, Retrieval-Augmented Generation, Generative AI, Agentic-AI, Data Lakes, Pyspark, Data Analytics, AutoGen, Data Management, Machine Learning Operations, Virtual Agents, Semantic Kernel, Data Pipelines, Human in the Loop, Databricks
- **Published:** October 12, 2026
- **Apply:** https://www.dice.com/job-detail/a9af2188-e8ba-4784-be91-b578ccdc3328

## About the Role

We are looking for a highly experienced Azure Databricks & Agentic AI Architect to design and lead next-generation AI-powered data platforms. The ideal candidate will have 15+ years of Data & Analytics experience, strong Azure Databricks/Lakehouse expertise, and hands-on experience with Generative AI, Agentic AI, and AI-driven Data Engineering., Experience leading enterprise AI transformation initiatives

Strong executive and client-facing communication skills

Ideal Candidate: A forward-looking architect who can combine Azure Databricks + Data Engineering + Generative AI + Agentic AI to build autonomous, intelligent, governed, and scalable enterprise data ecosystems.
Requirements
Required Skills

15+ years of Data & Analytics experience

Strong hands-on Azure Databricks

Lakehouse Architecture, PySpark, Spark SQL, Python & SQL

Azure OpenAI

Generative AI & Agentic AI

RAG Architecture

LangChain / LangGraph

MCP Protocol

AI Agent Orchestration

Vector Databases / Knowledge Graphs

Azure DevOps & CI/CD

MLOps / LLMOps

AI Testing & Evaluation Frameworks

## Description

Design enterprise-scale Azure Databricks Lakehouse platforms using Delta Lake, Unity Catalog, ADLS Gen2, Databricks Workflows, and Delta Live Tables.

Lead the implementation of Agentic AI for autonomous data ingestion, mapping, transformation, data quality, metadata enrichment, lineage, testing, and pipeline optimization.

Design AI-driven Data Development Lifecycle (AI-DLC) solutions covering requirements, data modeling, code generation, testing, documentation, deployment, and monitoring.

Architect RAG-based GenAI solutions using enterprise data.

Design AI agent orchestration using Azure OpenAI, LangGraph, LangChain, Semantic Kernel, AutoGen, and MCP.

Build domain-specific AI agents for Data Engineering and Analytics teams.

Design self-healing data pipelines and AI-driven incident triage, failure prediction, SLA monitoring, capacity planning, and cost optimization.

Establish Human-in-the-Loop (HITL) frameworks and governance for autonomous AI agents.

Define enterprise AI governance covering security, observability, auditability, prompt governance, cost monitoring, and responsible AI.

Mentor architects, data engineers, and AI engineers.

Lead enterprise architecture discussions and communicate AI strategy and business value to senior/CXO stakeholders.