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

InPost

3d•Remote

About The Position

We're looking for a Staff Software Engineer to raise the quality bar across our mobile app and backend domain - not by owning a test suite, but by changing how the whole domain designs, ships, and trusts its software. This is a hands-on technical leadership role. You'll shape architecture for testability and reliability, own the quality gates that let teams release with confidence, and build a culture where engineers own quality rather than hand it off. You'll operate as a true Staff Engineer: setting technical direction across several teams, going deep in the codebase when it matters, and framing quality as an engineering and business outcome - not a QA phase at the end. If you've done this in a product with real mobile scale, even better. Your scope of work will cover 3 areas. I. Quality architecture & engineering Set and own the quality and reliability strategy across the domain - from the API/contract layer through to native iOS (Swift/SwiftUI) and Android (Kotlin) clients. Design for testability and release confidence: quality gates inside release and store-deployment pipelines, device and OS-version fragmentation coverage, and flakiness control at scale (BrowserStack + GitLab CI). Keep the backend/API/contract layer strong and connect it cleanly to the mobile client layer. Drive resolution of quality and reliability issues that cross team boundaries within the domain. Get hands-on in the codebase where your depth moves the needle - prototypes, tooling, reference implementations, thorny incidents. II. Technical leadership, coaching & culture Shift quality ownership left into the engineering workflow - be the person teams pull in before implementation starts, not after. Mentor senior engineers across the domain and accelerate real, visible growth. Run knowledge-sharing across the org: tech talks, workshops, reusable documentation, pair sessions; co-lead the OneTech community. Co-shape the domain's technical direction with the SEM , with full autonomy within the domain, and analyse quality trends from metrics to identify where to improve. Define quality and reliability metrics and gates , and use them to frame risk in business terms for EMs, SEMs, and PMs. III. AI governance in engineering Define how AI is adopted for quality and engineering productivity in the domain — which tools, which workflows. Design AI-assisted workflows and set governance and data-security standards across teams. Assess and manage the risk of AI usage (including production-facing work), not just the productivity upside. Mentor engineers on responsible, effective AI use and report on its ROI.

Requirements

8+ years of software engineering experience , with a track record operating at Staff / Principal / Tech Lead / Architect level - proven impact beyond a single team (standards set for multiple teams, or a cross-team initiative led).
Deep ownership of quality and reliability as an engineering discipline - you've set standards and designed testing/quality strategy (not just executed someone else's plan) and changed outcomes measurably.
Proven shift-left experience - entering the process before code is written and measurably moving the result.
A strong hands-on engineering foundation - you can read, review, and write production-quality code, and teams respect your technical depth.
Experience leading technical and process change directly with development teams.
A hands-on, critical relationship with AI - using it and assessing its risks, not just its benefits.
Fluent English .

Nice To Haves

Commercial, working-level experience building or testing native mobile apps (Swift and/or Kotlin) at real scale - a major bonus for this role.
Experience with BrowserStack and CI/CD (GitLab) .
Snapshot testing experience (e.g. swift-snapshot-testing, Paparazzi) and introducing mock-based testing standards.
Experience in the logistics or e-commerce industry.
Fluency in Polish .
Familiarity with Appium (useful for understanding what we're migrating away from).
Experience applying AI in engineering / testing workflows .
ISTQB Advanced Level – Test Automation Engineer certification.

Responsibilities

Set and own the quality and reliability strategy across the domain - from the API/contract layer through to native iOS (Swift/SwiftUI) and Android (Kotlin) clients.
Design for testability and release confidence: quality gates inside release and store-deployment pipelines, device and OS-version fragmentation coverage, and flakiness control at scale (BrowserStack + GitLab CI).
Keep the backend/API/contract layer strong and connect it cleanly to the mobile client layer.
Drive resolution of quality and reliability issues that cross team boundaries within the domain.
Get hands-on in the codebase where your depth moves the needle - prototypes, tooling, reference implementations, thorny incidents.
Shift quality ownership left into the engineering workflow - be the person teams pull in before implementation starts, not after.
Mentor senior engineers across the domain and accelerate real, visible growth.
Run knowledge-sharing across the org: tech talks, workshops, reusable documentation, pair sessions; co-lead the OneTech community.
Co-shape the domain's technical direction with the SEM , with full autonomy within the domain, and analyse quality trends from metrics to identify where to improve.
Define quality and reliability metrics and gates , and use them to frame risk in business terms for EMs, SEMs, and PMs.
Define how AI is adopted for quality and engineering productivity in the domain — which tools, which workflows.
Design AI-assisted workflows and set governance and data-security standards across teams.
Assess and manage the risk of AI usage (including production-facing work), not just the productivity upside.
Mentor engineers on responsible, effective AI use and report on its ROI.