Python, SQL, ETL/ELT, Data Modeling, Data Quality, Cloud-native Development, API Integration, Data Engineering, ETL, Document Processing, Workflow design, knowledge of LLM development, RAG, Prompt Engineering, AI Coding Assistants Advanced Skills: RAG Data Pipelines, LLM Data Integration, AI Service Integration, Scalable AI Deployments, Agent Orchestration, Tool Calling, LangGraph, LangChain

- Design and develop GenAI applications using Python and enterprise LLM platforms.
- Build scalable data pipelines for structured and unstructured data processing. 3.

Implement

Retrieval-Augmented Generation (RAG) systems and vector-based search solutions.
- Integrate LLMs with enterprise applications through APIs and workflows.
- Develop cloud-native AI services on AWS, Azure, GCP, Databricks (DBRX), or Snowflake.
- Create agent-based solutions using LangChain and LangGraph.
- Ensure data quality, governance, and security compliance across AI workflows.
- Optimize performance, scalability, and reliability of AI solutions.
- 1+ years of experience with Hugging Face, LangChain, OpenAI, Anthropic, Gemini, or open-source LLMs.
- Familiarity with knowledge graphs and semantic search. 3.

Experience building production-grade GenAI solutions

📌 Python ML_GenAI Engineers (Chennai)
🏢 Infosys
📍 Chennai