Senior Go developer

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.

You will be:

developing, enhancing, and maintaining multi-tenant backend services and APIs using Go (Golang), gRPC, Kubernetes, and PostgreSQL,

designing and optimizing data models, including canonical product data models, with a focus on performance and multi-tenancy,

designing APIs in accordance with Google AIP standards and architectural principles, ensuring scalability and proper multi-tenant support,

designing and presenting architectural changes through Architecture Decision Records (ADRs), following established guidelines and principles,

building and maintaining integrations between backend services and multiple SaaS systems, including product content management systems,

ensuring code quality through automated testing, code reviews, and adherence to engineering standards,

troubleshooting issues, optimizing performance, and providing L2 support for backend services,

collaborating with cross-functional teams in an agile development environment,

proactively monitoring service health, identifying and resolving production issues before they impact customers.

Your profile:

• strong experience in backend development with Go (Golang) 5+ years
• solid understanding of concurrency, data structures, and backend fundamentals,
• experience designing and consuming APIs,
• experience with SQL databases (PostgreSQL, MySQL or equivalent),
• proficiency with Git-based workflows,
• experience with unit and integration testing,
• hands-on experience with Docker,
• practical experience using AI-powered assistants (e.g. Claude Code, GitHub Copilot, Cursor) to improve productivity, quality, or decision-making in software delivery.

Nice to have:

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.