AI Engineer - Generative AI and Databricks Specialist

Infosys; Bengaluru; On-site; INR 2,500,000 - 4,500,000; Full time

Job summary

Infosys in Bengaluru is seeking an AI Engineer specializing in Gen AI and Databricks. You will design, develop, and optimize scalable data pipelines, leverage Spark/PySpark, Python, SQL, and Databricks to process structured and unstructured data, and deploy Generative AI solutions.

Collaborate with Data Scientists and engineers to implement RAG architectures, vector databases, and MLOps concepts, ensure data quality, governance, and security, and integrate AI workloads with cloud services and

Qualifications

• Experience in data engineering and GenAI is required.
• Design and build data pipelines using Databricks.
• Experience with Spark/ PySpark and SQL.
• Knowledge of Delta Lake and data warehousing concepts.
• Experience with Generative AI LLMs and retrieval-augmented generation.

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 architectures and vector databases.
• Work with large-scale datasets using Spark and PySpark.
• Integrate AI solutions with cloud services and enterprise apps.
• Collaborate with data scientists, engineers, and stakeholders.
• Monitor, troubleshoot, and optimize data and AI workloads.
• Ensure data quality, governance, and security standards.

Skills

Databricks/Data Engineering

GenAI / LLMs experience

PySpark / Apache Spark

Python

SQL

ETL/ELT Development

Data Pipeline Development

RAG Frameworks

Vector Databases

Git

Tools

Databricks

Spark / PySpark

Python

SQL

Git

Docker

CI/CD

REST APIs

Job description

AI Engineer (Gen AI, Databricks) Gen Ai + Databricks (with Data Engineering exp is preferred)

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

Key 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