Software Development Specialist

NTT DATA North America; Bengaluru; On-site; INR 2,500,000 - 4,300,000; Full time

Job summary

NTT DATA North America is seeking a QA Architect to design multi-agent testing workflows and reference architectures for AI-powered agents. You will integrate testing agents with CI/CD, test management, and observability platforms.

Role requires hands-on automation experience, proficiency in multiple programming languages, and strong QA governance. You will coach engineers and drive an AI-led QA transformation across the organization.

Qualifications

• Strong background in software testing and quality engineering.
• Hands-on test automation architecture experience.
• Proficiency in Python, Java, JS/TS, or C#.
• Experience with Selenium, Playwright, Cypress, REST Assured, Postman, and CI/CD tools.
• Understanding of LLMs, GenAI, prompts, agents, and guardrails.
• Ability to integrate testing solutions into CI/CD pipelines.
• Strong QA metrics, defect lifecycle, test strategy, and release governance.
• Excellent communication and stakeholder-management skills.

Responsibilities

• Design multi-agent QA workflows for test planning, design, automation, execution, reporting, and defect analysis.
• Build reference architectures for AI-powered testing agents.
• Integrate testing agents with test management, automation, CI/CD, source control, defect tracking, and observability platforms.
• Define prompt libraries, RAG patterns, tool-calling workflows, and agent orchestration models.
• Establish review and approval workflows for AI-generated test cases and automation code.
• Define evaluation metrics for agent output quality.
• Create reusable patterns for API, UI, regression, performance, and exploratory testing agents.
• Support testing of AI and GenAI-based applications.
• Implement governance for data privacy, security, auditability, and responsible AI usage.
• Coach QA engineers on AI-assisted testing practices.
• Partner with leadership to define an AI-led QA transformation roadmap.

Skills

Software testing

Quality engineering

Test automation architecture

Python

Java

JavaScript

TypeScript

C#

LLMs / GenAI concepts

CI/CD integration

QA metrics & release governance

Communication & stakeholder mgmt

Tools

Selenium

Playwright

Cypress

REST Assured

Postman

Karate

Jenkins

GitHub Actions

Azure DevOps

Jira

TestRail

Zephyr

Job description

Responsibilities

• Design multi-agent QA workflows for test planning, test design, automation, execution, reporting, and defect analysis.
• Build reference architectures for AI-powered testing agents.
• Integrate testing agents with test management, automation, CI/CD, source control, defect tracking, and observability platforms.
• Define prompt libraries, RAG patterns, tool-calling workflows, and agent orchestration models.
• Establish review and approval workflows for AI-generated test cases and automation code.
• Define evaluation metrics for agent output quality.
• Create reusable patterns for API, UI, regression, performance, and exploratory testing agents.
• Support testing of AI and GenAI-based applications.
• Implement governance for data privacy, security, auditability, and responsible AI usage.
• Coach QA engineers on AI-assisted testing practices.
• Partner with leadership to define an AI-led QA transformation roadmap.

Required Experience

• Strong background in software testing and quality engineering.
• Hands-on test automation architecture experience.
• Programming experience in Python, Java, JavaScript, TypeScript, or C#.
• Experience with tools such as Selenium, Playwright, Cypress, REST Assured, Postman, Karate, Jenkins, GitHub Actions, Azure DevOps, Jira, TestRail, Zephyr, or equivalent.
• Understanding of LLMs, GenAI, prompts, agents, RAG, embeddings, tool calling, and guardrails.
• Experience integrating testing solutions into CI/CD pipelines.
• Strong understanding of QA metrics, defect lifecycle, test strategy, and release governance.
• Excellent communication, architecture documentation, and stakeholder-management skills.