Qa Automation Lead(Automation+AI Testing)-5-10Yrs-Mumbai

Crescendo Global Leadership Hiring India; Mumbai; Hybrid; INR 1,800,000 - 3,200,000; Full time

Job summary

Linedata’s AI Competency Center seeks a Senior QA Lead to own quality across the solution lifecycle, from exploration to production. You will work with AI/ML, product, DevOps, and security teams to define testing strategies, automate validation, and ensure data integrity and reliability.

This role emphasizes GenAI, RAG, and non-deterministic applications, requiring hands-on QA leadership and a collaborative mindset to elevate engineering quality across FinTech solutions.

Qualifications

• 5–10 years of hands-on QA/QA engineering experience.
• Experience with web, API, database, and end-to-end testing.
• Proficiency in Python, Java, or JavaScript/TypeScript for test automation.
• Experience integrating tests into CI/CD pipelines.
• Strong understanding of Agile SDLC and risk-based testing.

Responsibilities

• Define risk-based QA strategies across prototypes, POCs, pilots, and production-ready solutions.
• Plan and execute functional, exploratory, API, UI, database, regression, performance, security testing.
• Design, develop, and maintain automated test suites for applications, APIs, workflows, and regression scenarios.
• Review requirements and designs to identify quality risks early.
• Test AI/GenAI applications for accuracy, reliability, and failure scenarios.
• Integrate automated testing into CI/CD pipelines and improve coverage and efficiency.

Skills

QA/QC testing

Automation testing

API testing

Selenium

Python/Java/JS

Tools

Selenium

Playwright

Cypress

Postman

REST Assured

Job description

Senior QA Lead AI Competency Center

MUMBAI, INDIA | 5–10 YEARS EXPERIENCE

Build quality into the next generation of enterprise technology

Linedata’s AI Competency Center explores new ways of solving business problems through software engineering, AI/ML, GenAI, automation, data, cloud, and modern application development. The center takes ideas from experimentation and proof‑of‑concept stages through validation and, where successful, toward production‑ready solutions.

As a Senior QA Engineer, you will help ensure that these solutions are reliable, secure, scalable, and production‑ready. You will work across engineering, product, AI/ML, DevOps, security, and financial‑domain teams to identify risks early, establish effective testing strategies, automate validation, and improve overall engineering quality.

The role also involves developing testing and evaluation approaches for emerging technologies such as GenAI, RAG, agentic systems, AI‑enabled workflows, and other non‑deterministic applications, where traditional testing approaches may need to be extended.

WHO ARE WE?

At Linedata we believe finance matters to our society as much as energy to life and fuelling financial transformation is vital for development and leadership. We humanize technology. We are passionate experts who provide the investment management and credit communities with innovative, user‑friendly products which help their businesses grow in over 50 countries.

We employ more than 1800 employees representing 40 nationalities spread throughout our offices in 14 countries. We believe in mobility, diversity & teamwork.

Our mission is to continue to find new ways to create and build flexible, mission critical software and services and to stay on the cutting edge of the financial software space.

ABOUT THE ROLE

Linedata’s AI Competency Center is seeking a Senior QA Engineer/Lead to own quality across the solution lifecycle, from early experimentation and development through validation and production. Quality in the Center goes beyond functional output to include code quality, APIs, databases, data integrity, performance, security, usability, reliability, and overall engineering practices.

This is not a traditional test‑execution role. You will work alongside software engineers, AI/ML engineers, product owners, DevOps, security teams, and financial‑domain experts to identify risks early, design effective testing strategies, automate validation, investigate complex defects, and establish quality practices for emerging technologies.

The Center works across AI/ML, GenAI, agentic systems, workflow automation, data platforms, cloud, modern web applications, and other emerging technologies, with applications across the FinTech domain.

WHAT YOU’LL DO?

• Define and drive risk‑based QA strategies across prototypes, POCs, pilots, and production‑ready solutions.
• Plan and execute functional, exploratory, API, UI, database, integration, regression, performance, security, usability, and end‑to‑end testing based on project needs.
• Design, develop, and maintain automated test suites for applications, APIs, workflows, integrations, and regression scenarios.
• Apply the right balance of manual and automated testing based on risk, coverage, repeatability, stability, and business value.
• Review requirements, acceptance criteria, architecture, code, APIs, databases, data flows, logs, and technical designs to identify quality and testability risks early.
• Validate not only application output but also data integrity, business rules, error handling, integrations, performance, scalability, reliability, and operational readiness.
• Investigate defects using technical evidence such as code, logs, APIs, databases, browser tools, and traces, and contribute to root‑cause analysis.
• Test AI/ML and GenAI applications for accuracy, relevance, consistency, robustness, hallucination, prompt behaviour, safety, and failure scenarios.
• Develop appropriate testing and evaluation approaches for RAG pipelines, agentic systems, tool calling, workflow automation, and other non‑deterministic applications.
• Integrate automated testing into CI/CD pipelines and continuously improve coverage, reliability, and execution efficiency.
• Evaluate and adopt modern and AI‑enabled testing tools for test generation, automation, defect analysis, test‑data generation, visual testing, and application evaluation.
• Identify quality risks in emerging technologies and develop appropriate testing approaches even when requirements or expected behaviour are still evolving.
• Establish quality gates and communicate quality risks, residual risks, and release‑readiness recommendations to technical and business stakeholders.
• Identify recurring quality issues and improve testing processes, tooling, environments, documentation, and engineering practices.
• Mentor engineers and QA professionals on testing, automation, defect investigation, and quality engineering.

WHAT YOU’LL NEED?

• 5–10 years of proven, hands‑on experience in QA, Software Testing, Quality Engineering, SDET, or a related role.
• Strong practical experience in both manual and automated testing, with experience designing and implementing effective test strategies.
• Hands‑on experience with web application, API, integration, database, regression, and end‑to‑end testing.
• Strong experience with automation frameworks and tools such as Selenium, Playwright, Cypress, REST Assured, Postman/Newman, PyTest, or equivalent.
• Ability to read, understand, debug, and contribute to code in Python, Java, JavaScript/TypeScript, or an equivalent language.
• Strong SQL and database‑testing skills, including data validation, relationships, transactions, and data integrity.
• Good understanding of APIs, authentication, integrations, logging, monitoring, error handling, retries, timeouts, and common application failure modes.
• Experience integrating automated tests into CI/CD pipelines and working with version‑controlled codebases.
• Strong understanding of Agile methodologies, SDLC, defect lifecycle, test design, and risk‑based testing.
• Strong analytical and problem‑solving skills with the ability to investigate defects beyond their symptoms.
• Ability to work independently, challenge unclear requirements, anticipate risks, and take ownership of quality outcomes.
• Ability and willingness to learn new technologies and adapt testing approaches to unfamiliar architectures and evolving requirements.
• Strong communication and collaboration skills, with the ability to influence developers, product teams, and other stakeholders.

GOOD TO HAVE:

• Experience testing AI/ML, GenAI, LLM, RAG, agentic systems, or AI‑driven workflows.
• Experience with AI‑assisted testing, AI evaluation frameworks, prompt testing, or AI‑powered QA tools.
• Exposure to performance testing tools such as JMeter, k6, Gatling, or equivalent.
• Familiarity with cloud platforms such as Azure/AWS, Docker, Kubernetes, Git, observability, or Infrastructure as Code.
• Exposure to security, accessibility, compatibility, mobile, or resilience testing.
• Experience in FinTech, capital markets, asset management, or other regulated environments.
• Experience establishing QA standards, automation frameworks, quality gates, or testing practices across multiple projects.
• Relevant testing certifications are desirable but not mandatory where strong practical experience is demonstrated.