Description

Build and maintain GenAI solutions, RAG systems, and AI agents for data analysis and enterprise integration.

This role is hybrid.

Responsibilities

• Develop GenAI-powered solutions for natural language queries, including Text-to-SQL and Text-to-Code capabilities.
• Build RAG-based systems using enterprise data, metadata, and business documentation.
• Design AI agents and agentic workflows for dataset discovery, code/data generation, and validation.
• Implement CI/CD pipelines, Infrastructure as Code (Terraform/CloudFormation), and monitoring for AI workloads.
• Integrate LLMs with enterprise platforms and APIs using Python and SQL.

Required Skills

• 6–10+ years in AI/ML, Data Engineering, or Software Engineering.
• Strong hands-on experience with GenAI, LLM applications, and prompt engineering.
• Proficiency in Python and SQL for data processing and analytics.
• Experience with RAG, AI agents, or Agentic AI frameworks.
• Hands-on experience with AWS cloud services and Amazon Bedrock or equivalent LLM platforms.
• Strong understanding of APIs and AI integration patterns.
• Experience with Terraform or CloudFormation for Infrastructure as Code.
• Knowledge of data governance, security, and DevOps practices.

Preferred Skills

• Experience with LangChain, LangGraph, or similar frameworks.
• Knowledge of vector databases and AWS Glue, Athena, S3, or Redshift.

Key Skills

Education

Bachelor's degree