Software Development Specialist

NTT DATA, Inc.; Chennai District; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

NTT DATA, Inc. in Chennai, India seeks a senior lead/developer to architect and build autonomous AI systems using agents, LLMs, and cloud services. You will lead design, development, and deployment of scalable AI solutions for enterprise workloads.

Expect hands-on coding in Python, deep cloud expertise (AWS/Azure), and leadership across cross-functional teams. You will implement production-grade pipelines, governance, and performance tuning in a fast-paced environment.

Qualifications

• Strong Python expertise with 8+ years preferred.
• Hands-on with LLMs and agent frameworks.
• Experience with AWS and Azure cloud services.
• Knowledge of REST APIs, microservices, and event-driven architecture.
• Familiarity with Git, CI/CD, Docker, Kubernetes.
• Experience deploying AI systems in production environments.
• Familiarity with AI governance, model evaluation, and monitoring.

Responsibilities

• Design and implement agent-based AI systems using frameworks like LangChain, LangGraph, AutoGen, CrewAI, Semantic Kernel, or similar.
• Develop multi-agent orchestration with memory, planning, and tool usage.
• Integrate LLMs into enterprise workflows (OpenAI, Azure OpenAI, Anthropic, open-source).
• Build secure, production-grade prompt engineering frameworks.
• Develop scalable backend services using Python (FastAPI, Flask, Django).
• Create 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.
• Lead AI architecture discussions and solution design workshops.
• Mentor junior developers and AI engineers.

Skills

Python

LLMs

Agent frameworks

APIs

AWS

Azure

REST

Microservices

Event-driven

Git

CI/CD

Docker

Kubernetes

Production AI

Governance

Tools

REST APIs

Job description

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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

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.

Build secure, production-grade prompt engineering frameworks.

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.

Design and deploy AI solutions on AWS:

SageMaker

Bedrock

Lambda

ECS/EKS

API Gateway

DynamoDB / RDS

Implement AI workloads on Azure:

Cognitive Services

Build secure cloud architectures with IAM, VPC, networking, and encryption best practices.

Implement infrastructure as code (Terraform, CloudFormation, Bicep).

Set up CI/CD pipelines for AI applications.

Implement model monitoring, logging, and performance optimization.

Ensure governance, compliance, and responsible AI practices.

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:

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.

Experience deploying AI systems in production environments.

Familiarity with AI governance, model evaluation, and monitoring.