GEN AI Manager

EY; Bengaluru; Hybrid; INR 2,500,000 - 5,000,000; Full time

Job summary

EY is seeking an experienced AI Developer (Python) in Bengaluru to design and implement advanced AI solutions. You will work with LangChain, LLM frameworks, and vector search to build scalable, enterprise-grade AI applications and agentic systems.

The role requires deep expertise in Python, API design, and cloud-native deployments, with a focus on secure data handling, performance optimization, and governance practices. On-site collaboration is essential.

Qualifications

• Proficiency in Python and AI/ML engineering.
• Experience with LLM frameworks, agentic AI architectures, and prompt engineering.
• Hands-on with vector databases and retrieval strategies for enterprise AI.

Skills

Python

Prompt Engineering

LLM Architecture

Multi-Agent Workflows

Tools

LangChain

LangGraph

AutoGen

Google Agent SDK

Model Context Protocol

Agent Frameworks

Vector Search (RAG)

Job description

AI Developer (Python) Experience 8- 13 years experienceSkills 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.