QA LEAD (QA 4)

Lepton Software

Gurugram District

On-site

INR 4,000,000 - 7,000,000

Full time

2 days ago

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Job summary

Lepton Software, a leader in Location Intelligence and GIS solutions, is seeking a QA Lead (QA 4) to transform quality engineering with GenAI, automation, and modern QA practices. You will define the QA strategy across products, drive shift-left testing, and establish release readiness standards.

This role emphasizes AI-assisted test generation, test data creation, and automated frameworks. The candidate will own Jira workflows, build dashboards, and ensure traceability between stories, tests,

Qualifications

8–12 years in QA with strong automation experience.
Experience integrating testing into CI/CD pipelines.
Deep expertise in Jira workflows, dashboards, and reporting.
Ability to define quality gates and release criteria.

Responsibilities

Create test strategies, plans, and scenarios (Functional, Regression, Integration, UAT).
Coordinate with product and engineering for acceptance criteria.
Drive performance testing using tools like JMeter, k6, etc.; validate under load and edge conditions.
Collaborate on security testing and vulnerability assessments.
Own defect management and quality insights; build dashboards and reports.

Skills

QA Automation

GenAI in QA

Jira Workflows

CI/CD

Performance Testing

Leadership

Observability

Education

Bachelor's in CS/Engineering

ISTQB certification

Tools

TestRail

Zephyr

Job description

Lepton Software is a leading provider of Location Intelligence, Smart Mapping, and GIS-based software solutions, empowering enterprises across Telecom, BFSI, Government, Retail, and Automotive sectors. With over 25+ years of expertise, Lepton delivers innovative geospatial products, network planning solutions, and enterprise-grade digital transformation services across global markets. Our culture encourages ownership, collaboration, continuous learning, and customer-centric innovation.

(A) JOB SUMMARY

We are looking for a QA LEAD (QA 4) who will transform quality engineering by leveraging Generative AI, automation, and modern QA practices. This is not a traditional QA role. The candidate will:

Drive AI-assisted test case generation and test optimization
Own quality processes, Jira workflows, and release governance
Enable engineering teams to adopt continuous testing and shift-left practices

The ideal candidate combines strong QA fundamentals + automation expertise + practical use of GenAI tools to improve speed, coverage, and efficiency.

Define and own the quality engineering strategy across products
Drive shift-left testing, continuous testing, and automation-first culture
Establish quality benchmarks, SLAs, and release readiness standards
Standardize QA processes across teams and projects

2. GenAI-Driven Testing (Critical)

Leverage Generative AI tools (e.g., LLMs, Copilot, internal AI tools) to:
- Generate test cases from requirements, PRDs, and user stories
- Auto-create test scenarios, edge cases, and negative test coverage
- Assist in test data generation and synthetic data creation
- Test case optimization and deduplication
- Impact analysis (what to test based on code changes)
- Defect pattern analysis and prediction
Build internal workflows/prompts/frameworks to scale GenAI usage across QA

3. Test Automation & Frameworks (Critical)

Design and implement scalable automation frameworks:
- UI (Selenium, Cypress, Playwright)
- API (REST Assured, Postman, Karate)
Drive high automation coverage for regression and critical paths
Ensure maintainability, reusability, and speed of automation suites

4. Jira & QA Process Ownership (Critical)

Own and optimize Jira workflows for QA lifecycle:
Ensure clear traceability between user stories, test cases, and defects
Define defect lifecycle, severity classification, and SLAs
Build dashboards and reports for:
- Test coverage
- Defect leakage
- Release quality metrics
Drive discipline in sprint QA processes and release governance

5. Test Planning & Execution

Create comprehensive test strategies, test plans, and test scenarios
- Functional
- Regression
- Integration
- UAT
Coordinate with product and engineering for acceptance criteria

6. Performance, API & Non-Functional Testing

Drive performance testing using tools like JMeter, k6, etc.
Validate system behavior under load, stress, and edge conditions
Ensure API reliability and contract validation
Collaborate on security testing and vulnerability assessments

7. Defect Management & Quality Insights

Analyze defect trends and perform root cause analysis
Reduce defect leakage into production through preventive measures
Provide actionable insights to engineering and product teams
Enable developers to adopt unit testing and test automation practices
Mentor QA engineers on automation, GenAI usage, and best practices
Build a lean, high-impact QA team (less manual, more automation)
Promote “quality as a shared responsibility” across teams

9. Observability & Continuous Improvement

Define and track quality KPIs (coverage, escape rate, flakiness, MTTR)
Continuously improve QA processes using data and insights
- Test impact analysis
- Risk-based testing
- Continuous quality monitoring

Core QA & Automation

8–12 years in QA with strong automation experience
Experience integrating testing into CI/CD pipelines

GenAI in QA (Must-Have)

Practical experience using GenAI tools for testing workflows
Ability to:
- Use AI for test optimization and coverage improvement
- Build reusable prompts/workflows for QA teams
Understanding of how AI improves speed, coverage, and efficiency in QA

Jira & Process Excellence