Docket is building AI-powered experiences that help go-to-market teams identify, understand, and engage high-intent buyers. We are looking for a detail-oriented Manual QA Engineer to help make our product reliable, intuitive, and ready for customers.
REQUIRED TO APPLY: Try our AI agent and answer both questions
Before submitting your application, you must:
1. Open the Docket agent and have a conversation with it:
Explore the Docket agent
2. Explore its responses and test how it behaves.
3. Answer both application questions using examples from your own conversation, including what you asked and how the agent responded.
Your application is incomplete without this interaction and both answers. No coding is required.
What you will do
• Test web-based AI product features across functional, regression, usability, and edge-case scenarios.
• Create and maintain clear test plans, test cases, and release checklists.
• Validate AI workflows, including prompts, generated outputs, tool integrations, and failure handling.
• Partner with Product, Design, and Engineering to clarify requirements and identify risks early.
• Reproduce, document, and prioritize bugs with precise steps, expected behavior, actual behavior, and supporting evidence.
• Perform exploratory testing to uncover issues not covered by predefined test cases.
• Verify fixes and support release readiness across staging and production environments.
• Help improve QA processes, defect triage, and product-quality standards as the company scales.
What we are looking for
• 2+ years of manual QA experience for SaaS or web applications.
• Strong understanding of software-testing fundamentals, including functional, regression, integration, smoke, and exploratory testing.
• Experience testing APIs, browser-based applications, and third-party integrations.
• Comfort evaluating AI-powered features, where outputs may vary and quality includes relevance, safety, and user experience.
• Excellent written communication and a disciplined approach to bug reporting.
• Ability to work independently, manage competing priorities, and collaborate in a fast-moving startup environment.
• Familiarity with tools such as Linear, Jira, Postman, browser developer tools, and test-management platforms.
Nice to have
• Experience testing B2B SaaS, CRM, marketing, sales, or analytics products.
• Exposure to automated testing frameworks or an interest in growing into automation.
• Experience with LLM evaluation, prompt testing, or AI safety and quality workflows.
• Basic SQL, API, or frontend debugging knowledge.
What success looks like
• Releases ship with clear quality coverage and known risks documented.
• Customer-impacting defects are identified before production whenever possible.
• Product teams have fast, actionable feedback throughout development.
• QA processes become more repeatable and scalable as Docket grows.
How we will evaluate your answers
We will look at how you connect product behavior to user needs, support your conclusions with evidence, distinguish observations from assumptions, and prioritize concerns. One well-investigated finding is more useful than a long list of unsupported observations. Finding a severe bug is not required.
Required before you submit
Open the Docket agent and complete the required interaction before answering the two questions below:
Explore the Docket agent
Both answers must be based on your own interaction with the agent. Include what you asked and how it responded. Aim for roughly 500 words across both answers.
If customization controls are available on the page, change one setting and compare the behavior before and after. Record the setting you changed and how you checked its effect.
