JumpCannon is an AI-powered commercial decision platform for food and beverage manufacturers selling into the foodservice market. It brings together distributor reports, product and customer information, and foodservice expertise. Its AI assistant, Lucy, helps users investigate performance, explore opportunities, and develop commercial plans based on their business data.
We’re looking for a Middle QA Engineer to test the JumpCannon web platform end to end.
Responsibilities:
- Test user journeys from file uploads to dashboards and interactions with Lucy.
- Validate processed data against source files, including rows, columns, values, dates, units, and totals.
- Test duplicate uploads, overlapping reports, missing data, unsupported formats, and incomplete reporting periods.
- Verify dashboard calculations, filters, comparisons, exports, and consistency across the platform.
- Evaluate Lucy’s responses for factual accuracy, grounding in authorized data, relevance to the selected business context, and honest handling of uncertainty.
- Test frontend behavior, backend APIs, integrations, authentication, and user permissions.
- Verify data isolation between customer companies and access within each company.
- Design and maintain automated tests for critical workflows and regression risks.
- Document defects clearly, investigate root causes with developers, verify fixes, and report coverage and release risks.
- Use controlled test environments and appropriate test data to protect original files and customer information.
Required skills and experience:
- Practical QA experience with web applications.
- Strong exploratory, functional, integration, and regression testing skills.
- Hands-on experience with Playwright or Cypress.
- Experience testing APIs with Postman or automated test code.
- Working knowledge of SQL.
- Confidence working with Excel, CSV, and other structured data files, including reconciling calculations with source data.
- Ability to write and maintain test code in TypeScript, JavaScript, or Python.
- Familiarity with Git, issue tracking, and collaborative development workflows.
- Ability to distinguish UI defects, data quality issues, calculation errors, and integration failures.
- Strong analytical thinking, attention to detail, clear written communication, and ability to prioritize testing by business impact.
- Upper-Intermediate English.
Preferred experience:
Experience with analytics platforms, BI tools, dashboards, data ingestion pipelines, AI assistants, commercial metrics, CI pipelines, Docker, cloud-hosted applications, performance, accessibility or security testing, or multi-tenant SaaS. Foodservice, distribution, or manufacturing knowledge is helpful but not required.
What success looks like:
Uploaded files produce accurate, traceable results; dashboards, exports, and Lucy’s answers match the underlying evidence; customer data stays protected; critical workflows have reliable regression coverage; and release decisions are based on clear test results and known risks.
How to apply:
Please share your CV and a brief summary of your QA experience, including the types of applications you have tested, the automation tools and programming languages you have used, and an example of a challenging defect you investigated and how you verified the fix.
Aaaaand, of course, your salary expectations :)
