Full Description

We are looking for a Quality Engineering leader to build and govern enterprise-level testing strategies across multiple teams and projects. The role is responsible for leading the QA practice, defining test architecture and automation standards, and ensuring consistent quality across UI, API, data, and AI-driven systems. This position combines strategic ownership with architectural oversight, mentoring teams, influencing stakeholders, and driving scalable, future-ready quality solutions

Role: Lead QA (Gen AI - Must Have)

Mandatory Skills: Gen AI, Python, Backend/API test automation

Experience: 10-15 Years

Location: Bengaluru or Mumbai Preferred

Must-Have Skills 5–7 years of experience leading QA teams or test practices 5+ years of hands-on Selenium automation experience with strong coding skills in Java or Python Proven expertise in test strategy, quality governance, and test metrics Experience designing and governing automation frameworks and test architecture Strong command over UI, API, backend, and database testing Solid understanding of API contract validation, integration testing, and data integrity Practical exposure to AI / LLM testing, including prompt validation and response evaluation Ability to mentor, coach, and grow senior testers and automation engineers Strong stakeholder communication and release quality ownership

Good-to-Have Skills Experience testing AI agents, multi-turn workflows, and ML pipelines Performance and scalability testing strategy ownership Data pipeline validation and backend-heavy system testing Experience driving test transformation or QA modernization initiatives Exposure to large-scale or enterprise systems (SaaS, fintech, data platforms) Experience working in Healthcare domain

Tech Stack

UI Automation: Selenium, Playwright

Automation Languages: Java or Python ,JavaScript, TypeScript

API Testing: Postman, REST Assured

API Technologies: REST, GraphQL, WebSockets

AI / LLM Testing: Lang Chain, Lang Graph, Agentic workflows

CI/CD: Jenkins, GitLab CI, GitHub Actions

Data & Backend: SQL, ETL pipelines (Airflow, Spark)

Performance Testing: JMeter , k6

Cloud Platforms: AWS or Azure

Key Responsibilities

Define Test Strategy & Quality Governance: Own and govern the end-to-end quality strategy across UI, API, backend, data, and AI-driven systems.

Test Data & Data Governance: Lead test data strategy, validation, and governance across environments, pipelines, and AI workflows.

People Leadership & Capability Building: Mentor QA leads and senior engineers, review test designs and automation code, and uplift overall testing maturity.

Stakeholder Influence & Release Decisions: Act as the quality authority, providing risk assessments, metrics, and go/no-go recommendations to leadership.

Lead Automation & Test Architecture: Architect and standardize Selenium- and Playwright-based automation frameworks using Java/Python, integrated with CI/CD pipelines.

Drive API, Backend & Data Quality: Establish standards for API contract testing, integration testing, database validation, and data consistency across microservices.

AI / Agentic System Testing Strategy: Lead testing approaches for LLM- and agent-based systems, including prompt behavior, hallucination detection, bias, and safety risks.