Jobs at InPost

Manage and maintain WAN, SD-WAN, LAN, and WLAN infrastructure; monitor performance and scalability; implement network solutions and devices; troubleshoot connectivity; configure routing, switching, Wi-Fi, security, and VPNs; automate network tasks; create standards and documentation; support technical teams; and travel as needed for projects and operations.

Build and maintain ETL/ELT pipelines, data layers, and models using SQL, Python, PySpark, Databricks, Azure, Data Lake, and Delta Lake. Ensure data quality through validation, monitoring, alerting, and incident diagnosis. Optimize Spark and SQL processes for performance and scalability, provide trusted data to analytical and product teams, document data processes and lineage, and translate business requirements into technical solutions while responsibly validating AI-assisted work.

Design and implement high-performance Java microservices using Spring Boot, Kafka, PostgreSQL, Docker, Kubernetes, and GCP. Own features from requirements through production, contribute to architecture and technical documentation, maintain code quality and CI/CD practices, address technical debt, collaborate with stakeholders, and mentor engineers. The role supports either an e-commerce payments platform or a merchant-facing core platform.

Set iOS technical direction for a unified multi-market consumer application across several mobile teams. Own architecture, modularization, concurrency adoption, security, build systems, quality standards, and technical roadmaps. Collaborate with product, backend, platform, QA, Android, and other engineering leaders. Drive cross-team technical decisions, mentor senior engineers, resolve disagreements, establish governance, and deliver platform improvements across a large production codebase.

Own and advance the evaluations platform for InPost’s production conversational AI shopping assistant. Responsibilities include LLM-judge pipelines, evaluation datasets, Polish-language golden sets, root-cause analysis, abuse and anomaly detection, reproducible release gates, and eval-driven development. The role provides technical leadership, establishes platform direction, mentors engineers, collaborates with product and business stakeholders, and translates quality goals into measurable definitions.

Own end-to-end recruitment for Tech, Data, and AI roles. Partner with hiring managers on role definition, sourcing, interviews, hiring decisions, candidate experience, and recruitment strategy. Provide talent-market insights, build candidate pipelines, use recruitment data to optimize processes, and support employer branding. The role requires strong technology recruiting expertise, structured interviewing, stakeholder management, and understanding of backend, frontend, cloud, and data roles.

Own the vision, roadmap, backlog, and delivery of AI-powered products. Translate business challenges into scalable solutions, define KPIs and business cases, prioritize initiatives, manage stakeholders, drive adoption, and measure business impact. Collaborate with AI engineers, data teams, IT, security, and governance stakeholders to develop reusable AI capabilities across markets and functions.

Leads the organization-wide Platform Engineering strategy and roadmap, spanning Platform Delivery, CloudOps, DevOps, SRE, Developer Experience, and AI Foundations. Drives architectural decisions, cloud-native standards, self-service platform capabilities, and migration from on-premises infrastructure to GCP. Establishes a unified internal developer platform, supports secure AI adoption, influences cross-functional technical decisions, and mentors senior engineering talent.

Own complex, cross-team technology programs from planning through launch, managing dependencies, risks, roadmaps, KPIs, governance, and measurable business outcomes. Coordinate engineering, product, design, operations, and leadership stakeholders while ensuring security, reliability, and operational readiness. Use AI to automate program management tasks, mentor associate TPMs, and improve delivery standards. The role requires strong technical program management, analytical, communication, Agile, and stakeholder-influence skills in an international e-commerce and logistics environment.

Designs and delivers enterprise-scale Microsoft Dynamics 365 and Power Platform solutions across international teams and markets. Leads architecture, integrations with Azure and enterprise systems, platform upgrades, migrations, and environment modernization. Mentors engineers, promotes engineering excellence and AI-enabled practices, contributes to technical strategy, and represents initiatives in architecture reviews and technical communities.

Administer and configure CRM platforms, including pipelines, custom objects, permissions, workflows, integrations, and automations. Translate parcel-machine deployment and partner onboarding processes into scalable CRM logic. Maintain data quality through audits, deduplication, validation, and lifecycle management. Build dashboards and reports for international stakeholders, gather cross-market requirements, and create documentation, training materials, and user support processes.

Own the technical roadmap and evolution of InPost’s cloud-based data platform across Azure and Databricks. Drive scalability, reliability, security, operational excellence, FinOps, cost optimization, DevOps/DataOps, CI/CD, and Infrastructure as Code practices. Manage technology vendors, procurement, contracts, SLAs, licensing, budgets, purchase orders, and invoices. Partner with Data, AI, Engineering, Finance, and business stakeholders across multiple markets.

Staff Software Engineer responsible for quality and reliability strategy across backend APIs and native iOS and Android applications. The role includes designing testable architectures, quality gates, release pipelines, device and OS coverage, flakiness controls, cross-team incident resolution, technical leadership, mentoring, quality metrics, and AI governance. The engineer will influence multiple teams, contribute hands-on code and tooling, and promote shift-left quality ownership across the engineering organization.

Design, develop, maintain, and deploy Java backend applications and microservices. Build scalable features, improve performance, security, and reliability, troubleshoot issues, participate in code reviews, document systems, and collaborate with cross-functional teams. The role also involves supporting continuous improvement and knowledge sharing in Agile/Scrum environments.

Analyze large-scale, real-time data across marketing, product, customer, sales, and logistics domains. Gather stakeholder requirements, develop scalable data models and analytics solutions, process data using Python/PySpark and SQL, and create actionable insights and recommendations. Build and maintain high-quality code, support data-driven decisions, coordinate visualizations, and collaborate with data engineers, data scientists, business analysts, and business stakeholders.

Lead a 10–15-person multidisciplinary AI engineering team and own the Group-wide AI Engineering strategy. Build AI-native products and backend platforms, establish development standards including CI/CD with evaluations and test sets, guide multi-agent and streaming workflows, improve architecture and engineering processes, and partner with product, data, vendors, and technology stakeholders. Responsibilities also include hiring, team development, budgeting, and influencing AI product direction across the organization.

Lead and develop an engineering team while driving greenfield initiatives and large-scale software projects from concept through production. Provide technical leadership in Java, architecture, system design, and modern engineering practices. Partner with Product Managers and stakeholders, manage delivery, communicate risks, support organizational change, and improve development processes. The role requires strong people leadership, cloud-native experience in GCP or AWS, product ownership, AI tool proficiency, and effective communication.

Lead technology due diligence, post-acquisition integration, and technology preparation for new market launches. Coordinate teams, systems, processes, budgets, milestones, dependencies, and stakeholder alignment across international markets without direct authority. Assess technology gaps, drive adoption of group standards, manage external partners, and develop integration playbooks, templates, reporting, and knowledge resources.

Own and develop InPost Pay fast-checkout products, including checkout and BNPL solutions. Translate customer needs into product requirements and user stories, manage tactical and strategic backlogs, and lead initiatives from concept through launch. Collaborate with technology, UX, data, marketing, stakeholders, and vendors; monitor market trends and competitors; use analytics, A/B testing, and research to guide decisions; and mentor team members.

Design and deploy data science and machine learning solutions for large-scale parcel delivery operations. Responsibilities include routing and allocation algorithms, vehicle and route optimization, graph-based analysis, clustering, regression, forecasting, and production model deployment. The role translates logistics and business problems into scalable data solutions that improve delivery speed, cost efficiency, and customer experience.