Software Development Senior Analyst

NTT DATA North America; Chennai District; On-site; INR 3,000,000 - 5,400,000; Full time

Job summary

NTT DATA North America in Chennai, India, seeks a Senior Software Development Specialist with 8+ years IT experience and strong hands-on AWS and AI solution expertise. You will develop, deploy, and support P2A initiatives and Agentic AI systems in production environments.

The role emphasizes building RESTful APIs (FastAPI/Flask), IaC with Terraform/CloudFormation, CI/CD pipelines, and collaboration with architects and DevOps to ensure secure, scalable, and cost-efficient AWS implementations.

Qualifications

• 8+ years of overall IT experience.
• 4–5 years of hands-on AWS experience.
• 1–2 years of experience in AI/GenAI solution development.

Responsibilities

• Design, develop, and deploy scalable applications on AWS.
• Implement cloud-native architectures using serverless and container-based services.
• Develop Infrastructure as Code (IaC) using Terraform / CloudFormation.
• Implement CI/CD pipelines and DevOps best practices.
• Develop AI‑powered applications leveraging LLMs and foundation models.
• Write clean, production-grade Python code.

Skills

Python

AWS

GenAI

LangChain

Terraform

CloudFormation

REST APIs

FastAPI/Flask

Docker

Kubernetes

SageMaker

Bedrock

Education

Bachelor's degree in CS/Engineering

AWS Associate certification

AI/ML certifications

Tools

Terraform

CloudFormation

Docker

Git

CI/CD tools

Job description

Job Description:

Grade 9- Software Development Senior Specialist

Role Description:

We are looking for a highly skilled Senior Developer with 8+ years of overall IT experience and strong hands‑on expertise in AWS cloud development and AI‑driven solution engineering. The candidate will play a key role in developing, deploying, and supporting AWS Platform-to-Application (P2A) initiatives and Agentic AI‑based enterprise solutions.

This role requires strong coding capabilities, real‑time AWS deployment experience, and practical exposure to Generative AI and Agentic AI systems. The ideal candidate should be execution‑focused, technically strong, and capable of working independently in production environments.

Role Responsibilities:

• AWS Development & Deployment
• Design, develop, and deploy scalable applications on AWS.
• Implement cloud-native architectures using serverless and container-based services.
• Support AWS P2A deployment activities under architectural guidance.
• Develop Infrastructure as Code (IaC) using Terraform / CloudFormation.
• Implement CI/CD pipelines and DevOps best practices.
• Ensure secure, resilient, and cost‑optimised AWS implementations.
• Participate in environment setup, configuration, and production releases.
• Troubleshoot and resolve production issues in real‑time deployments.
• Agentic AI & AI Solution Development
• Develop AI‑powered applications leveraging LLMs and foundation models.
• Implement RAG (Retrieval-Augmented Generation) pipelines.
• Build and integrate multi‑agent workflows and orchestration logic.
• Integrate vector databases for contextual AI applications.
• Work with AWS Bedrock / SageMaker for AI model integration.
• Implement prompt engineering techniques and AI evaluation strategies.
• Ensure production readiness, monitoring, and logging of AI solutions.
• Application Engineering
• Develop REST APIs and microservices (FastAPI / Flask preferred).
• Write clean, maintainable, and production‑grade Python code.
• Implement secure authentication and authorization mechanisms.
• Perform unit testing, integration testing, and performance tuning.
• Collaborate with architects, DevOps teams, and AI specialists.
• Participate in code reviews and technical discussions.

AWS (Strong Hands‑On Experience Required)

• Minimum 4-5 years of hands‑on AWS experience.
• Core services: EC2, S3, Lambda, API Gateway, RDS, DynamoDB.
• Networking basics: VPC, Security Groups, Load Balancers.
• Containerization: Docker, EKS/ECS.
• IAM roles and security best practices.
• Monitoring: CloudWatch.
• Infrastructure as Code: Terraform or CloudFormation.
• Experience in real‑time production deployments.

AI / GenAI / Agentic AI

• Experience developing LLM‑based applications.
• Hands‑on experience with LangChain / LangGraph / LlamaIndex or similar frameworks.
• RAG implementation.
• Vector databases (FAISS, Pinecone, OpenSearch, pgvector).
• Understanding of embeddings, tokenization, and prompt engineering.
• Exposure to multi‑agent or workflow orchestration frameworks.
• Experience integrating OpenAI / Bedrock / similar foundation models.

Programming

• Strong proficiency in Python (mandatory).
• Experience with REST APIs (FastAPI / Flask).
• Familiarity with Git and CI/CD tools.
• Strong debugging and troubleshooting skills.

Desired Skills

• Experience with AWS Bedrock or SageMaker.
• Kubernetes exposure.
• Event‑driven architecture (SNS/SQS/Kafka).
• Knowledge of AI model monitoring and guardrails.
• Experience with frontend frameworks (React/Angular).
• Exposure to DevSecOps practices.
• Knowledge of database optimization (SQL/NoSQL).

Behavioral & Professional Traits

Technical Execution

• Strong hands‑on developer mindset.
• Ability to independently handle development and deployment tasks.
• Detail‑oriented and quality‑focused.

Problem Solving

• Strong debugging and root cause analysis skills.
• Ability to work in production support scenarios.

Communication Skills

• Good verbal and written communication.
• Ability to interact with architects and senior stakeholders.
• Ability to clearly articulate technical issues and solutions.

Collaboration

• Works effectively in Agile teams.
• Proactive in identifying risks and proposing solutions.
• Willingness to learn emerging AI technologies.

Experience requirement:

• 8+ years of overall IT experience.
• 4-5 years of AWS hands‑on experience.
• 1-2 years of experience in AI/GenAI solution development.
• Experience working in enterprise‑level production environments.

Educational Qualification

• Bachelor’s degree in Computer Science, Engineering, or related field.
• AWS Associate certification preferred.
• AI/ML certifications are an added advantage.