About the Role
Executive Assist Co. places skilled professionals with founders and growth-stage companies across the US, Australia, and New Zealand. We are hiring a QA Engineer to join one of our client teams full time.
You will work on a high-throughput messaging platform that handles the full lifecycle of a campaign: carrier registration, phone number provisioning and management, message building and sending, and detailed metrics and tracking. The product was built and proven as an internal tool, and it is now being developed into a standalone SaaS product, with new differentiating features and engineering for scale underway.
What You Will Do
This role sits at the intersection of QA, engineering, and product. We are looking for an expert in test automation who also has the product sense to understand how the application actually gets used, not just how it works mechanically.
In practice, you and the product manager should become the two people who understand real customer flows and what correct results look like better than anyone else on the team, including the engineers. The engineers know how their own features work. You will know how the system is supposed to behave end to end, and you will be the one who can tell a genuine defect apart from expected behavior.
You will start by testing manually, because that is how you learn the system deeply and figure out exactly what needs to be checked. From there you automate it, writing down the manual steps clearly enough that AI tooling can help you build out the scripts while you move on to the next thing. Manual testing never fully goes away, especially for brand new features, but the goal is a first-class automated suite that frees the team from re-checking the same ground every release.
Responsibilities
- Manual and release testing. A big part of the role, shared closely with the product manager rather than owned outright. Manually test new features before release, focusing on the full range of scenarios including the unhappy paths, not just the happy path. Help drive release preparation and post-release testing: running code freezes, identifying what has changed and what needs checking, building and running smoke and regression tests, and making sure new work is genuinely ready to ship. A lot currently goes untested each release, and closing that gap is a big part of why this role exists.
- Test automation. Build and maintain automated test suites across API, web UI, and service-to-service layers, choosing the right level of test rather than defaulting to brittle UI tests. The web interface is a natural place to start building automation early. Use AI tooling to accelerate this wherever it helps, but be able to write and modify the code yourself when the tooling needs it.
- Own the test and proxy API. Take ownership of the proxy and test environment that simulates message sending. Today different engineers have each built pieces of this for their own work, and it has drifted away from reality. We want one person who owns it, keeps it updated as new functionality ships, and makes it emulate real production conditions as closely as possible. The aim is realistic testing, not artificially over-stressing the system, since over-testing a dynamic system creates pressure in places that would not see it in production.
- Bug reproduction and reporting. Reproduce issues reported by clients and end users, pin down what actually triggers the problem, and document it clearly with the evidence engineering needs, such as reproduction steps, trace IDs, log excerpts, and metrics, so they can act without re-investigating. A good chunk of reported bugs turn out to be confusion rather than defects, so part of the value is sorting one from the other.
- Performance and load testing support. Set up the framework and configuration for performance and load tests, run them on a schedule, and help facilitate reviewing the results so the team can act on them. Engineers still own performance testing of their own work and fixing what surfaces. You provide the tooling, run the comprehensive tests, and serve as the subject matter expert they come to.
- Environment configuration and light DevOps. Configure and operate test and staging environments so tests run reliably: scheduling automated runs through CI, making sure jobs kick off and hit the right environment with the right keys, and inspecting queues and cloud metrics when something is not behaving in a distributed, queue-based setup.
- Process and collaboration. Work with the PM during requirements gathering to help document manual test cases as features are designed, and help improve the team's overall QA process over time.
What We Are Looking For
- Automation expertise (non-negotiable). We can help the right person develop product sense, and manual testing can be taught by showing someone the system. The skill we cannot easily build internally is real depth in test automation. You should be an expert with modern UI and API automation frameworks such as Playwright, Selenium, or similar, not someone learning them on the job. We are open to your view on the right tooling for the stack.
- Testing mindset and detail orientation. You write clear, complete test cases and reproduce bugs methodically. You are the kind of person who notices the scenario nobody else thought to check, and you document observations so precisely that engineering can act on them immediately.
- Distributed and event-driven systems. You understand producer/consumer and pub/sub patterns and their specific failure modes: consumer lag, message redelivery and duplication, poison messages and dead-letter queues, and what happens when one stage runs slower than its upstream. You can trace a single logical operation as it crosses multiple services and queues, reason about where a discrepancy was introduced, and tell a real defect apart from normal lag or eventual consistency. Debugging a monolith is one thing. Not missing anything in a system where events are passing around everywhere is another, and that is the skill that matters here.
- Engineering ability. Enough general engineering and scripting skill, in Python, JavaScript/TypeScript, or similar, to build your own tooling and harnesses, and to modify automation code so it works with AI agents rather than waiting on the engineering team to do it for you.
- AI in the QA workflow. Comfort using AI tools to support testing and to help generate automation code. This is increasingly part of every engineering role, and the team leans into it.
- Product empathy. Whether you arrive with it or build it here, you will need a genuine feel for how the application is used in the real world, so you can look at data and behavior and know whether it is right.
Familiarity with the Stack
You do not need every one of these on day one, but you should be familiar with most of what is used and comfortable with these types of systems and tools:
- AWS as the cloud platform
- Lambda, including its limitations versus the real API
- JavaScript and TypeScript
- Queue-based systems such as BullMQ (comfort with similar systems matters more than the exact one)
- DocumentDB
- Redis
- Some DevOps familiarity for standing up environments and scheduling test runs
Nice to Have
- Experience testing streaming data pipelines or analytics systems
- Familiarity with infrastructure-as-code such as Terraform, CloudFormation, or CDK
- Familiarity with contract testing between services, such as Pact, and with chaos or fault-injection testing
- Experience validating real-time analytics pipelines for correctness under load
Engagement and Logistics
- Engagement type: Full-time contractor through Executive Assist Co.
- Location: Fully remote
- Working hours: US timezone overlap required
- Compensation: $900 - $1300
- Benefits and other details: Discussed during the hiring process
