Technical AI Product Engineer

EY; Chennai District, Bengaluru; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

EY in India seeks an AI Engineer to design GenAI-powered applications using LLMs, RAG, and agentic workflows. You will translate business problems into measurable AI-driven outcomes and define success criteria.

The role emphasizes building scalable AI systems, AI lifecycle management, and responsible, secure implementation. Collaborate with product, data, and engineering teams to prioritize AI features, influence architecture, and deliver reusable AI components and APIs across enterprise

Qualifications

• Bachelor’s or Master’s in Computer Science, AI/ Data Engineering, or related field.
• 2+ years of experience in AI engineering or development.
• Experience with GenAI patterns: Prompt engineering, Retrieval-Augmented Generation (RAG), Embeddings & semantic search, Agentic workflows.
• Experience deploying AI solutions on cloud platforms (Azure preferred).
• Strong programming in Python and SQL.

Responsibilities

• Design and develop GenAI-powered applications using LLMs, RAG, and agentic workflows.
• Translate business problems into measurable AI-driven outcomes.
• Define evaluation metrics and product success criteria.
• Build and optimize retrieval-augmented generation pipelines.
• Develop agent-based AI systems with tool usage and orchestration.
• Deploy solutions on cloud-native architectures (Azure preferred).
• Implement prompt engineering strategies, embeddings, and fine-tuning approaches.
• Build evaluation frameworks and guardrails for reliability and safety.
• Enable continuous monitoring of quality, latency, and cost.
• Embed responsible AI practices (bias detection, explainability, moderation).
• Ensure data privacy, governance, and compliance standards.
• Build systems aligned with enterprise security and trust principles.

Skills

Python

SQL

GenAI patterns

Embeddings & semantic search

Agentic workflows

PyTorch / TensorFlow

LangChain / Semantic Kernel

APIs integration

MLOps / GenAI Ops

Monitoring & observability

Education

Bachelor’s or Master’s in Computer Science, AI/ Data Engineering

Tools

Azure OpenAI

Azure ML

Azure DevOps

Docker

MLflow

Spark/Databricks

Job description

What Youll Do

Build AI Products, Not Just Models

• Design and develop GenAI-powered applications using LLMs, RAG, and agentic workflows
• Translate business problems into measurable AI-driven outcomes
• Define evaluation metrics and product success criteria

Engineer Intelligent Systems at Scale

• Build and optimize retrieval-augmented generation (RAG) pipelines
• Develop agent-based AI systems with tool usage and orchestration
• Deploy solutions on cloud-native architectures (Azure preferred)

Own the AI Lifecycle (GenAI Ops)

• Implement prompt engineering strategies, embeddings, and fine-tuning approaches
• Build evaluation frameworks and guardrails for reliability and safety
• Enable continuous monitoring of quality, latency, and cost

Drive Responsible & Secure AI

• Embed responsible AI practices (bias detection, explainability, moderation)
• Ensure data privacy, governance, and compliance standards
• Build systems aligned with enterprise security and trust principles

Collaborate & influence

• Partner with product, data, and engineering teams to prioritize AI features
• Influence enterprise AI architecture and best practices
• Enable teams through reusable AI components and APIs

What You Bring

Must-Have Skills

• Strong programming in Python and SQL
• Hands-on experience with GenAI patterns: Prompt engineering, Retrieval-Augmented Generation (RAG), Embeddings & semantic search, Agentic workflows
• Experience with AI/ML frameworks: PyTorch / TensorFlow, Hugging Face, LangChain / Semantic Kernel
• Experience deploying AI solutions on cloud platforms (Azure preferred): Azure OpenAI, Azure ML , Azure AI Search

Engineering & Platform Skills

• Strong foundation in data processing (Pandas, NumPy, Spark/Databricks)
• Experience with MLOps / GenAI Ops: MLflow, pipelines, CI/CD, Docker, Azure DevOps
• Experience building APIs and integrating AI into applications
• Understanding of monitoring, observability, and system reliability

Good-to-Have

• Experience building agent-based or autonomous AI systems
• Cost optimization for LLM workloads
• Multi-modal AI (text, image, voice)
• Frontend integration for AI-driven experiences

Qualifications

• Bachelor’s or Master’s in Computer Science, AI/ Data Engineering, or related field
• 2+ years of experience in AI engineering or development

Additional

• Certifications in AI, genAI or Ganetic AI
• Experience with data governance, security, and compliance standards