Key Responsibilities:

Test Automation & Framework Architecture

• Architect and maintain robust, reusable test automation frameworks for UI, API, and backend systems.
• Develop automated test suites using Playwright (primary), Selenium, PyTest, JUnit, or equivalent.
• Implement Page Object Model, Screenplay, or component-based design patterns for maintainable test code.
• Build data-driven and keyword-driven testing capabilities to support complex business scenarios.
• Integrate automated tests into CI/CD pipelines using Jenkins, GitHub Actions, or similar platforms.
• Implement shift-left testing practices — embedding quality gates early in the development lifecycle.
• Complete all assigned, mandatory training within the timeframe provided
• Conduct and/or participate in regularly scheduled 1:1 meetings with direct manager and/or direct reports

Performance, Load & Scalability Engineering

• Design and execute performance test strategies for critical systems: load testing, stress testing, spike testing, soak testing, and capacity planning.
• Build and maintain performance test suites using JMeter, Gatling, k6, Locust, or equivalent tools.
• Define performance baselines, SLAs, and acceptance thresholds for response time, throughput, error rate, and resource utilisation.
• Conduct bottleneck analysis using APM tools (Datadog, Dynatrace, New Relic, AppDynamics) and system-level profiling (CPU, memory, I/O, thread dumps, GC analysis).
• Execute scalability validation for microservices, APIs, and database layers under production-like traffic patterns.
• Integrate performance tests into CI/CD pipelines for continuous performance regression detection.
• Produce performance test reports with clear findings, recommendations, and risk assessments for stakeholders.

Quality Strategy & Collaboration

• Collaborate with cross-functional teams (developers, product, DevOps, SRE) to define test strategies, acceptance criteria, and quality goals.
• Analyse test results, identify root causes of failures, and drive resolution with development teams.
• Contribute to release planning and risk assessment by providing data-driven quality and performance insights.
• Mentor junior SDETs and QA engineers, promoting best practices in test design, automation, and performance engineering.
• Stay current with industry trends and emerging tools in test automation, performance engineering, and DevOps.

AI-Augmented Quality Engineering

• Leverage AI tools (GitHub Copilot, Cursor IDE, or equivalent) to accelerate test script development and maintenance.
• Explore and implement AI-assisted test case generation from requirements and user stories.
• Build or adopt AI-driven failure triage and root cause analysis workflows.
• Evaluate emerging AI testing tools and recommend adoption where they deliver measurable value

• Complete all assigned, mandatory training within the timeframe provided
• Conduct and/or participate in regularly scheduled 1:1 meetings with direct manager and/or direct reports

Skills & Technology Matrix

Category

Skills & Tools

Test Automation

Playwright (primary), Selenium WebDriver, REST Assured, PyTest, JUnit, TestNG, Cucumber/BDD

Programming

Java (strong), Python (strong), TypeScript, SQL

Performance Tools

JMeter, Gatling, k6, Locust, Artillery, Taurus, BlazeMeter

APM & Profiling

Datadog, Dynatrace, New Relic, AppDynamics, Grafana, JProfiler, VisualVM, async-profiler

Performance Analysis

Thread dump analysis, GC log analysis, heap profiling, CPU/memory/I-O bottleneck identification, database query profiling (EXPLAIN plans)

CI/CD & DevOps

Jenkins, GitHub Actions, GitLab CI, Docker, Kubernetes, Helm

API Testing

Postman, REST Assured, GraphQL testing, contract testing (Pact), gRPC testing

Cloud Platforms

AWS (EC2, ECS, EKS, CloudWatch, X-Ray), Azure (AKS, Monitor), GCP

AI Tooling

GitHub Copilot, Cursor IDE, AI-assisted test generation, LLM-based failure triage

Methodologies

Shift-left testing, TDD/BDD, risk-based testing, exploratory testing, chaos engineering principles

Monitoring & Observability

Prometheus, Grafana, ELK/EFK stack, CloudWatch, distributed tracing (Jaeger, Zipkin, OpenTelemetry)

Required Experience

Must-Haves

• 5+ years of experience in software engineering with a focus on test automation and quality.
• Strong software development fundamentals and production-grade coding skills in Java and/or Python.
• Hands-on test automation using Playwright (required) and Selenium.
• Proven experience across UI, API, and backend testing.
• CI/CD pipeline integration for automated testing (Jenkins, GitHub Actions, or equivalent).
• 2+ years of hands-on performance testing using JMeter, Gatling, k6, or Locust.
• Experience defining performance baselines, SLAs, and conducting bottleneck analysis with APM tools.
• Strong understanding of QA methodologies, test design patterns, and shift-left practices.
• AI-native mindset with demonstrated experience using AI tooling for test development.
• Experience mentoring junior engineers in test automation and performance engineering.

Nice-to-Haves

• Testing microservices and distributed systems at scale.
• Cloud platform experience (AWS, Azure, or GCP) for infrastructure-aware testing.
• Containerised environments (Docker, Kubernetes) for test environment management.
• Contract testing using Pact or similar frameworks.
• Chaos engineering experience (Gremlin, LitmusChaos, Chaos Monkey).
• Database performance tuning and query optimisation knowledge.
• AI-assisted test generation, predictive failure analysis, and intelligent test prioritisation.
• Experience with distributed tracing and observability for test diagnostics.

Mandate Skills (Per Intake Call)

Non-negotiable requirements confirmed during the hiring intake discussion:

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Mandate Skill

What We’re Looking For

1

5+ years in Automation Testing

Proven track record across multiple projects/employers, not just one long stint

2

Selenium / Playwright

Playwright is primary; Selenium experience shows breadth. Must have architected, not just used.

3

Development in Java / Python

Production-grade code, not just test scripts. Comfortable with OOP, design patterns, and code reviews.

4

AI for Code / Test Cases

Active usage of Copilot, Cursor, or equivalent. Can describe specific workflow changes, not just tool names.

5

Performance & Load Testing

Hands-on with JMeter/Gatling/k6. Can design load profiles, analyse bottlenecks, and present findings to stakeholders.