Summary
✨ AI‑Generated
Join an AI engineering team focused on turning ambitious ideas into scalable production systems. You will combine AI expertise with strong software engineering skills to build robust model deployment pipelines, GenAI applications, and agentic AI systems. Working alongside data engineers, architects, and business users, you will transform data and emerging AI capabilities into high-quality solutions with measurable business impact.
Highlights
Build scalable, production-ready AI solutions with a strong emphasis on engineering quality and measurable business value. The role provides exposure to modern GenAI and agentic AI systems, collaboration with multidisciplinary experts, and access to a broad engineering and cloud knowledge network.
Description
DOES THIS SOUND LIKE YOU?AI is your playground, engineering is your toolkit, and turning ambitious ideas into production systems is your idea of fun.
Sound familiar? Then we might just be looking for you!We’re building an AI team in Belgium — and we want you on it.
From our office right in the heart of Antwerp, you combine AI expertise with strong software engineering skills to build scalable solutions that deliver real, measurable business value for some of the country’s most innovative clients.
Robust model deployment pipelines, cutting-edge GenAI applications, agentic AI systems — you turn promising concepts into production-ready solutions with the latest technology in your hands.And you won’t do it alone.
You’ll work in cross-functional teams with data engineers, architects, and business users and tap into the wider Xebia network of software engineering and cloud experts whenever a challenge calls for it.
Together, you turn data into value while keeping the bar high on quality, scalability, and maintainabilityWHAT YOU WILL DO TO MAKE ORGANIZATIONS DATA-DRIVENThe Analytics Engineer is the bridge between business and analytics.
You understand what data can bring to the organization.
With your effective communication skills, you help uncover business needs and how to support them with data, reporting, and visualization.
You use software engineering best practices to write production-grade data pipelines, making high-quality data available for creating business value with analytics.
You leverage modern tooling to model, test, and document data.Your efforts enable data democratization by improving the reliability and accessibility of data products.
As an Analytics Engineer, you play a vital role in empowering end users to make data-driven decisions.Check out our website or one of our customer stories to get a more detailed understanding of what we do.Interested in learning more about how and why the role of Analytics Engineering emerged? You can read this blogpost from one of our Analytics Engineers!We’re known for something that rarely comes in one package: we innovate fast, and we actually ship.
Real industrialization, getting solutions into production instead of leaving them as impressive demos.
If you’re ready to build AI-driven applications that make a genuine difference for clients, this is your chance.WHAT WE ARE LOOKING FORAt Xebia, we solve real business problems with AI.
As an AI Engineer, you are a hands-on technical contributor who helps take AI solutions from an idea to production.
You collaborate closely with business users to understand the problem being addressed and identify the shortest path from data to value.
Your engineering skills enable you to create solutions that are robust, scalable, testable, maintainable, and easy to extend.
Responsibilities and tasksBuilding production-ready AI solutions that generate measurable business value.Developing scalable deployment pipelines using modern cloud and MLOps / LLMOps practices.Creating cutting-edge GenAI applications and agentic AI systems.Rigorously evaluating AI solutions to ensure they provide real value rather than remaining impressive demonstrations.Working with CI/CD pipelines, Infrastructure as Code, cloud platforms, and GenAI or LLM integrations.Collaborating with engineers, data scientists, business users, and other stakeholders throughout the development process.Using AI coding tools such as Copilot, Cursor, or Claude to work more effectively without compromising quality.Sharing your knowledge and using the collective expertise of your Xebia colleagues to solve challenging problems.Depending on your experience, you may take the lead on technical decisions and coach other engineers as they develop their expertise.Working with different clients, environments, systems, and business challenges.Examples of solutions delivered by Xebia’s AI Engineers include:Building a Market Intelligent Assistant (multi-agent system) that is used in practice and already delivers business value.Developing an LLM-based data-extraction solution that captures unstructured information from historical documents.Realizing an AI-powered self-service data onboarding solution that guides users through data preparation, validation, and enrichment using agent-based workflows.
