Staff Software Engineer in Test - mobile (m/f/n)

InPost is a leading out-of-home (OOH) e-commerce enablement platform in Europe, founded in 1999. It operates a network of over 64,000 Automated Parcel Machines (APMs) and 30,000 pick-up and drop-off points across nine European countries. In 2025, InPost delivered 1.4 billion parcels, offering environmentally friendly, flexible, and contactless delivery solutions.

Must-have:

• 8+ years software engineering experience at Staff, Principal, Tech Lead, or Architect level with cross-team impact.
• Experience testing on at least one mobile platform (iOS or Android) with commercial, working-level experience.
• Ownership of quality and reliability as an engineering discipline, including strategy design and outcome change.
• Proven shift-left experience impacting quality prior to code implementation.
• Strong hands-on engineering skills with ability to write and review production-quality code.
• Experience leading technical and process changes with development teams.
• Hands-on, critical experience with AI usage and risk assessment.
• Fluent in English.

Strong plus:

• Experience with BrowserStack and CI/CD (GitLab).
• Snapshot testing experience (e.g., swift-snapshot-testing, Paparazzi) and introducing mock-based testing.
• Experience in logistics or e-commerce industry.
• Fluency in Polish.

Nice-to-have:

• Familiarity with Appium.
• Experience applying AI in engineering/testing workflows.
• ISTQB Advanced Level – Test Automation Engineer certification.

Quality architecture & engineering:

• Set and own quality and reliability strategy across the domain from API to native mobile clients.
• Design for testability and release confidence with quality gates in release and deployment pipelines using BrowserStack and GitLab CI.
• Maintain strong backend/API layer connected to mobile clients.
• Drive resolution of cross-team quality and reliability issues.
• Hands-on coding including prototyping, tooling, and incident response.

Technical leadership, coaching & culture:

• Shift quality ownership left into the engineering workflow before implementation.
• Mentor senior engineers and run knowledge-sharing initiatives like tech talks and workshops.
• Co-lead the OneTech community and co-shape domain technical direction with SEM.
• Define quality and reliability metrics and use them to assess risk for EMs, SEMs, and PMs.

AI governance in engineering:

• Define AI adoption strategies for quality and productivity.
• Design AI-assisted workflows with governance and data-security standards.
• Assess and manage AI usage risks including production impact.
• Mentor on responsible AI use and report on AI ROI.