GEN AI Engineer

EY; Chennai District, Bengaluru; Hybrid; INR 1,400,000 - 2,600,000; Full time

Job summary

EY is seeking an AI Developer (Python) with 4-8 years of experience to design and build reusable AI components, agents, and scalable backend systems. The candidate will work with GenAI architectures, RAG pipelines, vector stores, and enterprise AI integrations in a cloud-native environment.

The role requires strong Python expertise, experience with LangChain-based tooling, and proficiency in modern AI governance and security practices while collaborating across product and engineering teams.

Skills

Python

LangChain

LangGraph

Auto Gen

Google Agent SDK

Model Context Protocol

Agent frameworks

LLM application

Agent architectures

Prompt engineering

Tool calling

Tools

Azure OpenAI

Azure AI Services

Docker

Kubernetes

OpenShift

FastAPI

REST API

Pinecone

FAISS

Redis Vector

pgvector

MongoDB

ClickHouse

Job description

AI Developer (Python) Experience 4-8 years’ experience

Skills and attributes for success

• Candidate must possess proficiency in the following technologies:
  • Core AI Engineering & LLM Frameworks
    Python, LangChain, LangGraph, Auto Gen, Google Agent SDK, Model Context Protocol, Skills-based agent frameworks.
  • GenAI / Agentic AI Systems
    LLM application development, agentic AI architectures, multi-agent workflows, prompt engineering, AI system design, tool/function calling, enterprise AI integration.
  • RAG, Embeddings & Vector Search
    Retrieval-Augmented Generation pipelines, embeddings, semantic search, context retrieval strategies, Azure AI Search, Pinecone, FAISS, Redis Vector, pgvector.
  • Backend & API Engineering
    Python, Fast API, REST API design, scalable API platforms, event-driven systems, microservices architecture, third-party system integration.
  • Cloud, Infrastructure & Containers
    Azure OpenAI, Azure AI Services, Docker, Kubernetes, OpenShift, cloud-native application development, containerized deployments.
  • Databases & Data Platforms
    SQL, NoSQL, MongoDB, Redis, ClickHouse, database design, performance optimization, data accuracy and integrity.
  • AI Model Engineering
    Model fine-tuning, LoRA, BERT, LLM architecture understanding, evaluation techniques, AI performance monitoring.
  • AI Governance, Security & Responsible AI
    PII protection, data privacy, AI security, compliance, responsible AI practices, governance controls, monitoring and observability frameworks.