• Design and implement tools and technologies to provision and configure an enterprise software system hosted in Kubernetes • Design and implement architecture and networking solutions within Azure • Automate/script existing processes using languages such as python and bash • Provision, configure, and maintain cloud resources using Terraform and Terragrunt • Actively monitor the application environment and respond to incidents • Conduct root cause analysis for production incidents • Oversee cloud infrastructure and recommend any potential improvements to technology or process • Contribute to team planning to solve engineering challenges • Be a dependable and highly skilled development resource for peers through education and review • Have a broad awareness of related projects and industry trends, and encourage innovative practices among peers • Provide detailed feedback and suggestions to team code reviews • Document and demonstrate solutions through written documentation, diagrams, and readable code

• Design and implement tools and technologies to provision and configure an enterprise software system hosted in Kubernetes • Design and implement architecture and networking solutions within Azure • Automate/script existing processes using languages such as python and bash • Provision, configure, and maintain cloud resources using Terraform and Terragrunt • Actively monitor the application environment and respond to incidents • Conduct root cause analysis for production incidents • Oversee cloud infrastructure and recommend any potential improvements to technology or process • Contribute to team planning to solve engineering challenges • Be a dependable and highly skilled development resource for peers through education and review • Have a broad awareness of related projects and industry trends, and encourage innovative practices among peers • Provide detailed feedback and suggestions to team code reviews • Document and demonstrate solutions through written documentation, diagrams, and readable code

• Design, develop, and support scalable data pipelines and cloud-native data architectures. • Build and maintain production-ready applications and data processing frameworks using Python, PySpark, Scala, and related technologies. • Partner with engineering and business stakeholders to deliver analytics-ready datasets and reporting capabilities. • Contribute to technical architecture decisions, platform improvements, and development best practices. • Develop and optimize ETL/ELT workflows and streaming data solutions. • Create and manage data models, reporting structures, and analytics dashboards using AWS-native tools. • Work with relational and NoSQL databases to support high-volume data processing and storage requirements. • Implement cloud infrastructure solutions leveraging AWS services and container orchestration platforms such as Kubernetes or ECS. • Collaborate with operations teams on backup, disaster recovery, data retention, and security strategies. • Participate in code reviews, technical mentorship, and collaborative problem-solving across the engineering organization. • Evaluate and recommend modern technologies and frameworks that improve scalability, efficiency, and reliability.

Role Description - Designing, building, and operating scalable Kubernetes-based platform infrastructure. - Developing backend platform services and reusable engineering components. - Building and maintaining cloud-native solutions (primarily on AWS). - Creating and evolving Infrastructure as Code solutions using Terraform. - Designing and implementing CI/CD pipelines and deployment automation. - Developing scalable multi-tenant platform capabilities for engineering teams. - Building self-service developer platform features and internal tooling. - Designing and maintaining APIs and platform architecture standards. - Improving platform reliability, observability, and monitoring capabilities. - Collaborating with engineering teams to improve developer experience and platform adoption. - Contributing to platform engineering best practices and technical standards. - Supporting container platform operations and orchestration processes. - Driving automation and operational excellence across the platform ecosystem. Qualifications - 5+ years of experience as a Platform Engineer. - Practical experience using AI-powered assistants (e.g. Claude Code, GitHub Copilot, Cursor) to improve productivity, quality, or decision-making in software delivery. - Strong hands-on experience with Kubernetes, including cluster operations and orchestration concepts. - Strong backend engineering background. - Strong programming skills in TypeScript and/or Go; Python experience is a plus. - Solid experience with cloud platforms, preferably AWS. - Practical experience with Infrastructure as Code tools, preferably Terraform. - Experience with CI/CD pipelines and deployment orchestration. - Experience designing scalable multi-tenant systems. - Strong understanding of API and platform architecture. - Solid Linux and networking fundamentals. - Experience with observability and monitoring solutions. - Experience building reusable self-service platform capabilities for developers. - Good English communication skills (at least B2 level). - Work from the European Union region and a work permit are required. Requirements - Experience applying GenAI in a more structured way within the SDLC, including defined workflows, prompt patterns, or tool integrations embedded into daily work. - Interest in and familiarity with emerging AI-driven practices (e.g. agent-based workflows, automation patterns, AI-augmented development), with a willingness to explore and experiment beyond standard approaches. - Experience with Internal Developer Platforms (IDP). - Experience building Kubernetes operators and controllers. - Experience with Backstage or developer portal tooling. - Experience in container runtime or platform engineering. - Knowledge of event-driven and distributed systems architecture. - Experience with service mesh technologies and OpenTelemetry. Recruitment Process - CV review - HR call - Technical Interview - Client Interview - Decision