Senior Engineering Manager; m​/f​/n Checkout

Senior Engineering Manager (m/f/n) – Payments & Checkout

Full-time

InPost Group (Euronext: INPST) is Europe's leading out-of-home e-commerce delivery platform, operating over 50,000 automated parcel machines (APMs) and PUDO points across Poland, the UK, France, Italy, and Benelux - processing tens of millions of transactions annually. Beyond logistics, InPost is building a full e-commerce services layer:
InPost Pay is our integrated checkout and payments product embedded directly into the merchant journey, with ambitions that extend into digital wallets, embedded finance, and AI-assisted commerce. This is fintech at logistics scale - and we are just getting started.

As you probably know, a lot is happening  build products and services that support millions of users and transactions every day. One of the key areas within our ecosystem is InPost Pay, where we develop solutions focused on digital payments, checkout experiences, and sales enablement.

We are looking for a Senior Engineering Manager who will take ownership of a growing engineering organization within the Pay domain. This is an opportunity for a leader who can scale teams, develop engineering leaders, drive technical excellence, and remain a credible partner in architectural and technology discussions.

• Driving the growth and scalability of technology teams supporting payment, checkout, and sales-related products.
• Leading an engineering organization of approximately 24–25 engineers across 3 teams:
  • two teams led through Engineering Managers,
  • one team managed directly.
• Developing Engineering Managers, Tech Leads, and senior engineering talent while building a strong leadership pipeline.
• Establishing and maintaining technical, architectural, and delivery standards across the entire domain.
• Shaping technology strategy in close collaboration with Product, Business, and Engineering stakeholders.
• Managing dependencies across teams and ensuring high-quality delivery at scale.
• Identifying and removing organizational and technical bottlenecks that impact product development and business outcomes.
• Defining and driving the domain's AI adoption strategy, identifying opportunities where AI can improve engineering productivity, software quality, and operational efficiency.
• Promoting responsible AI adoption, experimentation, and innovation across engineering teams while measuring business and engineering impact.
• Leading the organization through data-driven decision-making by defining, monitoring, and improving domain-level KPIs, OKRs, SLAs, and engineering performance metrics.
• Using engineering insights and metrics to continuously improve delivery effectiveness, platform reliability, team productivity, and customer outcomes.
• Representing the engineering organization in strategic initiatives and cross-functional leadership discussions.

• 10+ years of experience in software engineering and technology leadership.
• Experience managing Engineering Managers and multi-team engineering organizations.
• Strong technical foundation gained as a Software Engineer.
• Hands‑on experience with Java and Spring Boot.
• Excellent understanding of distributed systems, microservices, event‑driven architectures, and modern backend engineering practices.
• Experience working with cloud environments (Google Cloud is a strong advantage).
• Experience defining technical standards, SDLC processes, governance models, and engineering operating frameworks.
• Ability to translate engineering strategy into measurable business outcomes and effectively communicate with senior stakeholders.

• Hands‑on technical background in the Java ecosystem (Spring Boot) or equivalent enterprise microservices stack (e.g., .NET/C#); sufficient depth to be a credible technical partner in architecture reviews and engineering decisions.
• Experience with in a production environment.
• Experience operating in large‑scale product organizations.
• Proven success in building and scaling engineering organizations through leaders.
• Experience implementing or scaling AI‑enabled engineering practices and tools.
• Strong understanding of engineering metrics, KPIs, OKRs, and organizational…