Senior AI Engineer: Agentic AI, RAG & LLM Ops

NTT DATA, Inc.; Indianapolis (IN); Hybrid; USD 120,000 - 210,000; Full time

Job summary

NTT DATA, Inc. is seeking a Senior AI Engineer to join our team in Bangalore, India, focusing on agentic AI design, RAG applications, and scalable AI services.

You will develop AI assistants, knowledge pipelines, and enterprise-grade solutions across engineering, data science, and product teams. The role emphasizes software engineering best practices, CI/CD, observability, and responsible innovation to help clients transform complex data into actionable insights.

Qualifications

• Experience designing agentic AI workflows and AI assistants.
• Proficient with RAG architectures, embeddings, and vector stores.
• Strong Python development skills and CI/CD practices.
• Familiarity with cloud-native AI platforms and observability.

Responsibilities

• Agentic AI design and develop AI assistants and agentic workflows.
• Build and optimize RAG applications for enterprise use.
• Develop knowledge ingestion, extraction, and retrieval pipelines.
• Implement chunking, semantic search, and graph-based retrieval.
• Develop scalable AI services, APIs, and automation workflows.
• Create browser automation solutions with Playwright or Puppeteer.
• Deploy, monitor, and optimize containerized AI applications.
• Contribute to AI testing, evaluation, benchmarking and experimentation.
• Apply software engineering best practices: testing, CI/CD, observability.

Skills

Agentic AI Design

RAG & Retrieval

AI Engineering

LLM-based Apps

Data Processing

Software Engineering

Cloud Architecture

MLOps / LLMOps

Model Evaluation

Browser Automation

Tools

LangGraph

Haystack

OpenAI SDK

LanceDB

FalkorDB

Playwright

Puppeteer

vLLM

SGLang

Azure Container Apps

Docker

Python

Ray

Job description

NTT DATA, Inc. is seeking a Senior AI Engineer to join our team in Bangalore, India, focusing on agentic AI design, RAG applications, and scalable AI services.

You will develop AI assistants, knowledge pipelines, and enterprise-grade solutions across engineering, data science, and product teams. The role emphasizes software engineering best practices, CI/CD, observability, and responsible innovation to help clients transform complex data into actionable insights.