Job highlights

- 2-5 years experience with Databricks and Data Engineering; expertise in Large Language Models, Retrieval-Augmented Generation, PySpark, and cloud platforms
- Design, develop, and deploy Generative AI applications; build RAG solutions; develop scalable data pipelines; fine-tune and integrate LLMs; implement prompt engineering and AI governance; develop APIs; collaborate with teams; monitor model performance and follow MLOps practices

Role: Generative AI Engineer Databricks Experience: 2-5 Years

Employment Type: Full-Time

Job Summary

We are looking for a Generative AI Engineer with hands-on experience in Databricks and a robust background in Data Engineering. The ideal candidate should have expertise in building AI-driven applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and scalable data pipelines. Experience working with Databricks, PySpark, cloud platforms, and modern AI frameworks is highly preferred.

Key Responsibilities

- Design, develop,



and deploy Generative AI applications using Databricks and cloud platforms.
- Build and optimize RAG-based solutions leveraging vector databases and enterprise data sources.
- Develop scalable data pipelines using Databricks, PySpark, and Python.
- Fine-tune, evaluate, and integrate LLMs into business applications.
- Work with structured and unstructured datasets to support AI/ML use cases.
- Implement prompt engineering, model evaluation, and AI governance best practices.
- Develop APIs and microservices for AI model integration.
- Collaborate with Data Engineers, Data Scientists, and Business stakeholders to deliver AI solutions.
- Monitor model performance, latency, and scalability in production environments.
- Follow MLOps best practices for model deployment, experimentation, and monitoring.

📌 Databricks+ Gen AI (Pune)
🏢 Infosys
📍 Pune