Job Description
We are looking for a GenAI + Databricks Engineer with hands-on experience in Data Engineering and Generative AI solutions. The ideal candidate should have expertise in building scalable data pipelines, working with Databricks, Python, and cloud platforms, while enabling AI/LLM-based use cases for business applications.
Roles Responsibilities
- Design, develop, and maintain scalable data pipelines using Databricks.
- Build and optimize ETL/ELT workflows for structured and unstructured data.
- Develop and deploy Generative AI solutions using LLMs.
- Implement RAG (Retrieval-Augmented Generation) architectures and vector databases.
- Work with large-scale datasets using Spark and PySpark.
- Integrate AI solutions with cloud services and enterprise applications.
- Collaborate with Data Scientists, Data Engineers, and business stakeholders.
- Monitor, troubleshoot, and optimize data and AI workloads.
- Ensure data quality, governance, and security standards.
Mandatory Skills
- 2-5 years of experience in Data Engineering and/or GenAI
- Databricks
- PySpark / Apache Spark
- Python
- SQL
- Data Pipeline Development
- ETL/ELT Development
- Delta Lake
- Data Warehousing Concepts
- Generative AI
- LLMs (OpenAI, Azure OpenAI, Llama, Claude, etc.)
- RAG Frameworks
- Vector Databases
- Git
Technical Requirement
- Gen Ai + Databricks (with Data Engineering exp is preferred)
Additional Responsibility Preferred Skills
- Azure Databricks or AWS Databricks
- LangChain / LangGraph
- Azure OpenAI
- MLflow
- Kafka
- Airflow
- Snowflake
- DBT
- Knowledge of MLOps concepts
Good to Have
- Prompt Engineering
- Agentic AI
- Semantic Search
- REST APIs
- Docker
- CI/CD Exposure
Educational Requirement
- Bachelor of Engineering,BTech
Preferred Skills
- Technology->AI-Generative AI->Generative AI for Data Analytics,Technology->Data Engineering->Databricks
Service Line
