Senior Software Development Specialist - AI & Cloud

NTT DATA Global Delivery Services Ltd; Chennai; On-site; INR 1,800,000 - 2,400,000; Full time

Job summary

NTT DATA Global Delivery Services Ltd in Chennai seeks a Senior Agentic AI Lead/Developer to design, develop, and deploy autonomous agent-based AI systems leveraging LLMs, LangChain, and cloud-native architectures. Strong Python, AWS, and Azure experience with scalable AI frameworks is essential.

You will lead architecture discussions, mentor engineers, and collaborate with Product and Security teams to deliver enterprise-grade AI solutions.

Qualifications

• 8+ years of Python development experience in production systems.
• Experience building AI systems with LLMs and agent frameworks.
• Hands-on cloud experience with AWS and Azure, and modern AI tooling.

Responsibilities

• Design and implement agent-based AI systems with memory, planning, and tool usage.
• Develop scalable Python backend services and AI microservices, with CI/CD.
• Architect and deploy AI workloads on AWS and Azure, using Terraform or similar IaC.
• Lead architecture discussions and mentor engineers in AI adoption.

Skills

Python

LLMs

Agent frameworks

LangChain

LangGraph

AutoGen

CrewAI

Semantic Kernel

API integrations

Tools

Docker

Kubernetes

Terraform

CI/CD

Job description

Software Development Senior Analyst Role Overview

We are seeking a highly skilled Agentic AI Senior Lead / Developer to design, develop, and deploy advanced AI systems leveraging autonomous agents, LLMs, and cloud-native architectures. The ideal candidate will have strong expertise in Python , AWS , and Azure , and experience building scalable AI-driven solutions using modern AI frameworks and cloud services. This role combines hands-on development, architecture design, and technical leadership in delivering intelligent, autonomous, and multi-agent systems for enterprise use cases.

Key Responsibilities

• Agentic AI & LLM Development Design and implement agent-based AI systems using frameworks such as LangChain, LangGraph, AutoGen, CrewAI, Semantic Kernel, or similar. Develop multi-agent orchestration systems with memory, planning, and tool usage capabilities. Integrate LLMs (OpenAI, Azure OpenAI, Anthropic, open-source models) into enterprise workflows. Implement RAG (Retrieval-Augmented Generation) pipelines using vector databases. Build secure, production-grade prompt engineering frameworks.
• Python Development Develop scalable backend services using Python (FastAPI, Flask, Django). Build AI microservices and APIs for enterprise integration. Implement async processing, workflow automation, and event-driven systems. Ensure high-quality code with unit tests, CI/CD integration, and best practices.
• Cloud Architecture (AWS & Azure) Design and deploy AI solutions on AWS : SageMaker Bedrock Lambda ECS/EKS API Gateway DynamoDB / RDS Implement AI workloads on Azure : Azure OpenAI Azure ML Azure Functions Azure Kubernetes Service (AKS) Cognitive Services Build secure cloud architectures with IAM, VPC, networking, and encryption best practices. Implement infrastructure as code (Terraform, CloudFormation, Bicep).
• DevOps & MLOps Set up CI/CD pipelines for AI applications. Manage containerization using Docker & Kubernetes. Implement model monitoring, logging, and performance optimization. Ensure governance, compliance, and responsible AI practices.
• Leadership & Strategy Lead AI architecture discussions and solution design workshops. Mentor junior developers and AI engineers. Define AI adoption strategy and roadmap. Collaborate with cross-functional teams (Product, Cloud, Security, Data Engineering).

Required Skills & Qualifications

• Technical Skills Strong expertise in Python (8+ years preferred). Hands-on experience with LLMs and agent frameworks . Deep understanding of: Prompt engineering RAG architecture Vector databases (Pinecone, FAISS, Weaviate, Azure AI Search) API integrations Experience with AWS and Azure cloud services . Strong knowledge of REST APIs, microservices, and event-driven architecture. Experience with Git, CI/CD, Docker, Kubernetes.
• Cloud & AI Expertise Experience deploying AI systems in production environments . Familiarity with AI governance, model evaluation, and monitoring. Experience integrating enterprise data sources (SharePoint, SAP, CRM, etc.).
• Experience Level Senior Level