Platform Tech Lead

Xebia is a global AI-first, digital transformation, and engineering partner. With over 25 years of experience and a team of 5,000 professionals across 16 countries, we help organizations design and build scalable products, platforms, and data-driven solutions. 

We specialize in Artificial Intelligence, Data and Cloud, Intelligent Automation, and Digital Products, combining deep technical expertise with a strong focus on engineering excellence and a people-first culture.  

In the CEE region, we’re a team of nearly 1,000 experts delivering modern applications, data platforms, and AI solutions for clients such as McLaren, Aviva, Deloitte, Spotify, Disney, ING, UPS, Tesco, Truecaller, AllSaints, Volotea, Schmitz Cargobull, Allegro, InPost, and many, many more. We work with leading technologies including AWS, Azure, GCP, Databricks, and Snowflake, and combine strong engineering culture with a consulting mindset and a continuous focus on growth and knowledge sharing. 

• shaping the technical direction and architecture of a developer-focused platform, balancing scalability, developer experience, and business goals,
• collaborating closely with engineering teams to define platform capabilities, prioritize initiatives, and make architecture-informed product decisions,
• driving the evolution of a cloud-native platform built on Kubernetes, AWS, and modern infrastructure tooling,
• designing intuitive developer workflows that simplify application deployment, operations, and platform adoption,
• contributing to platform architecture, including areas such as multi-tenancy, deployment pipelines, identity and access management, and platform security,
• supporting the development of internal platform capabilities, including build and deployment systems, observability, and developer tooling,
• working in a fast-paced environment, rapidly validating ideas, delivering new capabilities, and iterating based on feedback,
• contributing hands-on to the codebase when needed, helping the team solve complex technical challenges.

• proven experience as a Technical Product Owner, Tech Lead, Platform Engineer, or in a similar role focused on developer platforms,
• experience building or evolving developer-focused platforms such as Railway, Vercel, Netlify, or similar cloud infrastructure products,
• strong understanding of cloud-native technologies, including AWS, Kubernetes, containers, and deployment pipelines,
• solid knowledge of platform architecture concepts, including multi-tenancy, control plane vs. data plane, and developer workflows,
• experience building products from the ground up (0→1) or within early-stage, rapidly scaling environments,
• strong product mindset with the ability to translate complex infrastructure into intuitive developer experiences,
• ability to collaborate effectively with engineering teams and make architecture-informed technical decisions,
• hands-on software engineering experience, ideally with TypeScript, NestJS, or similar backend technologies,
• understanding of API design, developer experience (DX) principles, identity and access management (IAM), security best practices, and cost optimization (FinOps),
• practical experience using AI-powered assistants (e.g. ChatGPT, Claude, Copilot Chat, or similar) to improve productivity, quality, or decision-making in analysis and software delivery.

Work from the European Union region and a work permit are required.

• hands-on experience with infrastructure tooling such as Terraform, Helm, Docker, and Kubernetes in production environments,
• familiarity with observability platforms such as Prometheus, Grafana, OpenTelemetry, or similar solutions,
• experience building or maintaining CI/CD pipelines, internal developer platforms, or Git-based development workflows,
• knowledge of billing, metering, or usage-based SaaS pricing models,
• familiarity with edge computing, CDNs, or high-performance networking architectures,
• previous experience building developer tools, APIs, or platform products,
• experience applying GenAI in a more structured way within the SDLC, including defined workflows, prompt patterns, or tool integrations embedded into daily analytical and documentation work,
• interest in and familiarity with emerging AI-driven practices (e.g. automation of analysis tasks, AI-supported documentation, or workflow optimization), with a willingness to explore and experiment beyond standard approaches.

CV review – HR call – Interview – Client Interview – Decision