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# Data Bricks AI Engineer

- **Company:** Saanvi Technologies
- **Location:** Juno Beach, FL, United States
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Unity 3d, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Databases, Python (Programming Language), Standard Sql, Search Technologies, SQL Databases, Pinecone, Enterprise Software Applications, LangChain, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Prompt Engineering, Generative AI, Agentic-AI, Build Management, Pyspark, CrewAI, Weaviate, AutoGen, Machine Learning Operations, FAISS, Claude, Semantic Kernel, GPT, Data Pipelines, ChromaDB, Databricks
- **Published:** November 3, 2026
- **Apply:** https://www.thejobnetwork.com/job/16c018bf-623a-4fea-bf00-7e91f8a8a30e/data-bricks-ai-engineer

## About the Role

* Strong experience with Databricks, PySpark, Python, and SQL
 * Expertise in Generative AI, LLMs, Prompt Engineering, and RAG
 * Experience building AI Agents and Multi-Agent Systems
 * Hands-on experience with LangChain, LangGraph, CrewAI, AutoGen, or similar frameworks
 * Knowledge of Vector Databases (Pinecone, ChromaDB, FAISS, Weaviate)
 * Experience with Azure, AWS, or GCP Cloud Platforms

## Description

Job DescriptionWe are seeking a Databricks AI Engineer with strong expertise in Databricks, PySpark, Generative AI, and Agentic AI to design and build intelligent, scalable AI solutions. The ideal candidate will have hands-on experience developing AI agents, RAG applications, and enterprise-grade data and AI platforms using Databricks. Key Responsibilities

 * Develop scalable data pipelines and AI solutions using Databricks, PySpark, Python, and SQL.
 * Design and implement Generative AI applications leveraging LLMs such as GPT, Claude, and Llama.
 * Build Agentic AI solutions using frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or Semantic Kernel.
 * Develop and optimize RAG (Retrieval-Augmented Generation) architectures using vector databases and embeddings.
 * Utilize Databricks Mosaic AI, MLflow, Unity Catalog, and Vector Search for AI application development and governance.
 * Integrate AI agents with enterprise systems, APIs, databases, and knowledge repositories.Implement LLMOps/MLOps practices for deployment, monitoring, and continuous improvement.