Data Engineer

workflows. Build resilient integration layers between AI components and internal systems (TMS, WMS, CRM, ERPs) using APIs, message queues and ETL processes. Develop and maintain RPA bots and automation scripts, ensuring secure credentials handling, observability and error recovery. Implement automated testing, CI/CD pipelines and deployment practices for repeatable, auditable releases. Establish monitoring, alerting and performance KPIs for automation and AI services; investigate incidents and drive corrective actions. Work with stakeholders to define business requirements, success metrics and adoption plans; provide training and documentation for end users and support teams. Identify opportunities for process optimisation and scalable automation, prioritising initiatives with clear ROI. Follow security, data protection and compliance standards when handling personal and operational data. Contribute to the continuous improvement of the automation platform, tools and best practices across

the organisation. Requirements Minimum 3 years' experience in software engineering, automation engineering or ML/AI engineering roles, preferably in logistics, supply chain or operations-driven businesses. Proven experience deploying AI or ML solutions to production and integrating them with business systems. Hands-on experience with RPA platforms (e.g., UiPath, Automation Anywhere, Blue Prism) and/or scripting automation using Python or similar languages. Strong backend development skills (Python/Java/Node.js), RESTful APIs, message brokers (e.g., Kafka, RabbitMQ) and containerisation (Docker, Kubernetes). Familiarity with ML tooling and model serving frameworks (e.g., TensorFlow Serving, TorchServe, MLflow) and feature engineering/ETL pipelines. Experience with cloud platforms (AWS, GCP or Azure) and infrastructure as code. Strong testing and CI/CD experience (Git, pipelines, automated tests) and an emphasis on observability and incident management. Excellent problem-solving, communication and stakeholder-management skills. Proactive, results-oriented and able to balance speed of delivery with operational robustness. Degree in Computer Science, Engineering, Data Science or equivalent practical experience. High level of English is required; additional languages are an advantage. Benefits Language platform Wellbeing programme Flexible working hours Online platform for lifelong learning Competitive salary Flexible remuneration services can be contracted Equal Opportunities Plan InPost has an Equal Opportunities Plan that promotes equality at all levels. We aim for equality in the company's workplaces, focusing on promotion, gender equality, diversity, equity and inclusion of people regardless of their abilities and conditions.

At InPost, we are accelerating our adoption of intelligent automation across operations to improve efficiency, reliability and scale. We are recruiting a Data Engineer to design, build and maintain automation solutions that leverage AI, machine learning and RPA to streamline processes across our logistics and customer experience platforms. Reporting to the Head of Automation & AI, this role is both technical and delivery-focused, partnering with cross-functional teams (Operations, Transport, IT, Product and Data Science) to translate business needs into robust, maintainable automation that delivers measurable impact. Responsibilities and Objectives Design, develop and deploy automation solutions combining machine learning models, rule-based logic and RPA tools to support operational processes (e.g., routing, exceptions handling, claims, forecasting). Collaborate with Data Science and ML Engineering to productionise models: feature pipelines, model serving, monitoring and retraining