[Hiring] Software Development Engineer in Test @CertifyOS

Role Description

We are looking for an AI-first Software Development Engineer in Test (SDET) to help us build reliable, scalable, and high-quality software. This role goes beyond traditional QA and test automation. You will leverage AI-assisted engineering and agentic workflows to accelerate test development, improve test coverage, automate quality checks, and identify performance and scalability issues. You will work closely with developers, product managers, and engineering leaders to embed quality throughout the software development lifecycle. We expect you to think like a software engineer, automate like an SDET, and use AI as a force multiplier.

Key Responsibilities

• AI-First Quality Engineering
  • Adopt AI-assisted and agentic approaches across the testing lifecycle.
  • Use AI coding agents to generate, execute, debug, and maintain automated tests.
  • Build AI-assisted workflows for test case generation from product specifications and acceptance criteria.
  • Explore agentic testing approaches that can independently execute workflows, identify failures, and report defects.
  • Use AI to analyse test failures, identify patterns, and suggest potential root causes.
  • Continuously identify opportunities to reduce manual effort through AI and automation.
• Test Automation
  • Build and maintain scalable automation frameworks for UI, API, integration, and end-to-end testing.
  • Develop reusable test components and automation libraries.
  • Automate critical business workflows and regression suites.
  • Integrate automated testing into CI/CD pipelines.
  • Use Playwright, Cypress, Selenium, or equivalent frameworks.
• Performance & Load Testing
  • Design and execute load, stress, spike, and endurance tests.
  • Simulate real-world traffic, concurrent users, and high-volume API requests.
  • Establish performance benchmarks and service-level objectives.
  • Identify bottlenecks across APIs, databases, microservices, and infrastructure.
  • Use tools such as k6, JMeter, Locust, or Gatling.
  • Analyse latency, throughput, resource utilisation, and error rates.
  • Work with developers to identify and resolve performance bottlenecks.
• Scalability & Reliability Engineering
  • Validate application behaviour as traffic, data volume, and workloads increase.
  • Identify scalability limitations across distributed systems.
  • Test asynchronous workflows, queues, event processing, retries, and failure recovery.
  • Evaluate database performance and query efficiency under load.
  • Identify resource constraints and potential points of failure.
  • Contribute to capacity planning and reliability improvements.
• Engineering Collaboration
  • Work with developers and product managers to identify quality risks early.
  • Participate in technical design and code reviews.
  • Define quality gates and automation standards.
  • Build a culture where quality is everyone’s responsibility.

Qualifications

• 3–6 years of experience in software testing and automation engineering.
• Strong programming skills in Python, Java, or JavaScript/TypeScript.
• Hands-on experience with Playwright, Cypress, or Selenium.
• Strong API automation and backend testing experience.
• Experience with performance testing tools such as k6, JMeter, or Locust.
• Understanding of microservices and distributed systems.
• Good knowledge of SQL and database testing.
• Experience integrating automated tests into CI/CD pipelines.
• Practical experience using AI coding assistants and AI agents.
• Ability to analyse logs, metrics, and performance bottlenecks.

AI & Emerging Engineering Practices

• Be comfortable working with AI coding agents such as Claude Code, Cursor, or GitHub Copilot.
• Use AI to generate test scenarios, automation scripts, and test data.
• Understand how to validate AI-generated code and prevent unreliable tests.
• Explore agentic workflows for autonomous test execution and failure analysis.
• Build reusable AI-powered testing workflows rather than relying only on manual prompting.

Good to Have

• Experience with AWS or GCP.
• Familiarity with Docker and Kubernetes.
• Experience with Kafka or other messaging systems.
• Exposure to Grafana, Prometheus, Datadog, or similar observability tools.
• Knowledge of chaos engineering and resilience testing.
• Experience with database performance tuning.

What Success Looks Like

• AI-assisted automation across critical product workflows.
• Reduced manual testing and regression effort.
• Faster feedback through automated quality gates.
• Reliable performance benchmarks for critical APIs and workflows.
• Early detection of performance and scalability bottlenecks.
• Improved release confidence as product traffic and data volumes grow.
• Continuous improvement in engineering productivity through AI adoption.

Benefits

• 100% coverage of health, dental, and vision insurance premiums for employees.
• Unlimited PTO, with at least two weeks off each year to recharge.
• Health insurance and statutory leave benefits for employees in India.
• Additional wellness (menstrual) leave for women.
• Commitment to building an inclusive environment where everyone feels valued.
• Pay transparency and encouragement of open compensation conversations.