About PeopleHum
peopleHum is a Human Capital Platform, built for the next decade, we're on a mission to transform The Future of Work. The winner of the 2019 Global Codie award, used by organizations around the world.
It is an intuitive, agile and integrated platform built for a complete multi-generational employee experience, from hiring to performance, engagement and HRMS, with the power of machine learning and automation.
Find out more - https://www.peoplehum.com
Role Overview
PeopleHum is an AI-native Human capital global platform built on a microservices architecture with event-driven pipelines and deep LLM integrations on the Java stack. We are looking for a QA Specialist who can own quality end-to-end from writing automation frameworks and API test suites to performance benchmarking and production monitoring using and for testing AI agentic systems. This is not a write test cases and throw them over the wall role. You will own the quality of features from requirement to production, collaborate directly with backend and frontend developers, and build the automation infrastructure that keeps our platform reliable. As our AI agents make autonomous decisions (payroll calculations, employee workflows, HR automation), testing their correctness, safety, and edge-case behavior is critical and we need someone excited by that challenge.
Key Responsibilities
Quality Ownership Mindset:
- You believe quality starts before a line of code is written not something tested for in the final phase
- You work to prevent defects, not just find them reviewing requirements and designs for testability before development begins
- You own quality culture on your team, not just test execution
- You are well versed with new age AI technologies for AI engineering and have show interest working in Agentic build environments.
- You are interested in vibe coding, AI and running QA As a service.
Advocacy & Risk Communication
- You are a quality advocate you raise concerns about risks early, suggest design changes that enhance testability, and don't stay silent when something feels off
- You communicate quality issues clearly to both technical and non-technical stakeholders, with data and impact, not just bug counts
- You have the confidence to push back on shipping when quality isn't there, while being pragmatic about deadlines
Collaboration & Partner, Not Gatekeeper
- You are embedded in the development team participating in sprint planning, stand-ups, and retrospectives with valuable insights, not just status updates
- You collaborate with developers during design and implementation, not just after code is written
- You bring both the developer and user perspective to conversations part detective, part engineer, part customer advocate
Critical Thinking & Analytical Skills
- You have a curious, analytical mindset investigating issues to their root cause, not just logging symptoms
- You think in edge cases identifying the scenarios that others miss and prioritizing testing based on risk and impact
- You can compromise between perfect coverage and good-enough results while staying flexible under pressure
Proactive Behaviour & Gap Identification
- You provide input on potential quality issues during the design phase before coding starts
- You continuously learn about new testing approaches, tools, and methodologies without waiting to be trained
- You identify flaws in processes and drive improvements, not just report them
Documentation & Communication Discipline
- You write clear, actionable bug reports with precise reproduction steps not vague descriptions
- You create test documentation that is understandable and maintainable by others on the team
- You articulate technical issues in a way that helps developers fix problems faster
Product Curiosity & User Empathy
- You think like a user understanding workflows, personas, and real world usage patterns to design meaningful test scenarios
- You are genuinely curious about the product, not just the test framework you want to understand what users care about and test accordingly
- You are excited by the challenge of testing AI agents that make autonomous decisions payroll, HR workflows, compliance where correctness isn't optional
Must have skills
- Strong hands-on experience with Selenium WebDriver, Playwright, and TestNG/JUnit is essential because this role expects end-to-end automation ownership.
- Solid knowledge of REST Assured, Postman, and API validation is a must, since the platform is built on microservices and AI-integrated services.
- Experience with Apache JMeter and understanding response times, throughput, SLA validation, and bottleneck analysis is very important.
- Good coding ability in Java is critical, with added value from Python and TypeScript/JavaScript for automation and test utilities.
- Since this is an AI-native platform, understanding LLMs, AI agents, non-deterministic outputs, guardrail testing, hallucination detection, and AI API testing is one of the biggest differentiators.
- Knowledge of Git, microservices, REST/Kafka communication, and SQL basics is necessary to test reliably in a real engineering environment.
Good to have skills
- Knowledge of Jenkins and GitLab CI/CD is very valuable because QA automation is much stronger when it is fully tied into build and deployment pipelines.
- Being able to run tests in containers and set up stable test environments is a big plus, especially in modern microservices-based products.
- Since the platform uses event-driven workflows, understanding how to test Kafka message production and consumption is highly useful.
- Experience with Cucumber/Gherkin or Robot Framework helps in writing clear, behavior-driven scenarios that improve collaboration between QA, developers, and product teams.
- Familiarity with Axe-core/WCAG validation and OWASP ZAP adds strong value because it improves both usability and product safety.
- Experience with tools like Claude Code, GitHub Copilot, Cursor, or Cody is a strong advantage for speeding up test automation and working efficiently in an AI-heavy engineering setup.
- Modern code-first performance testing tools are highly valuable because they fit well into CI/CD workflows and are more flexible for engineering teams than traditional load-testing setups.
- This is especially important in microservices-based systems because it helps validate API boundaries and prevents service-to-service integration issues early.
- A very strong plus because it enables isolated, Docker-backed test environments, making integration testing more reliable and production-like.
- A useful frontend-focused E2E testing tool with a strong developer experience, especially valuable for faster debugging and tighter collaboration with frontend teams.
- These are great to have because shift-left security scanning improves product quality early in the pipeline and reduces risk before release.
- This stands out because observability-driven testing is becoming very important in modern distributed systems, especially for tracing failures across services.
