Job Title : AI Engineer Databricks

Location : Chennai / Bangalore

About the Role :

We are seeking an AI Engineer with hands-on experience in building Generative AI and LLM-powered applications on Databricks. In this role, you will design, develop, and deploy scalable AI solutions using Mosaic AI and the Databricks Data Intelligence Platform for enterprise clients. You will work closely with data engineers, architects, and business stakeholders to deliver production-grade AI systems.

Key Responsibilities :

- Design and develop GenAI and LLM-based applications on Databricks

- Build RAG pipelines, AI agents, and conversational systems using Mosaic AI

- Deploy and manage LLMs using Databricks Model Serving

- Implement LLMOps best practices using MLflow for experiment tracking, versioning, and monitoring

- Optimize AI pipelines for performance, scalability, and reliability

- Ensure governance, security, and lineage of AI assets using Unity Catalog

- Collaborate with enterprise clients to understand requirements and deliver solutions

- Create technical documentation and support knowledge transfer

Technical Skills Required :

- Mosaic AI Agent Framework for compound AI systems and agents

- Mosaic AI Vector Search for RAG applications and semantic retrieval

- Databricks Model Serving endpoints (DBRX, Llama, MPT)

- MLflow for experiment tracking, model registry, and LLMOps

- AI Playground and Foundation Model APIs for rapid prototyping

- LangChain and LlamaIndex integration with Databricks

- Unity Catalog for AI governance, access control, and lineage

- PySpark and Pandas UDFs for distributed AI data processing

Experience & Qualifications :

- 3+ years of experience in AI/ML engineering

- At least 1 year of hands-on experience with Databricks

- Delivered 2+ production-grade AI solutions (RAG systems, chatbots, AI agents, etc.)

- Strong problem-solving and analytical skills

- Excellent communication skills for client-facing interactions and technical documentation

Nice to Have :

- Experience working with enterprise-scale data platforms