At FDJ UNITED, we don't just follow the game, we reinvent it.

FDJ UNITED is one of Europe’s leading betting and gaming operators, with a vast portfolio of iconic brands and a reputation for technological excellence. With more than 5,000 employees and a presence in around fifteen regulated markets, the Group offers a diversified, responsible range of games, both under exclusive rights and open to competition. We set new standards, proving that entertainment and safety can go hand in hand. Here, you’ll work alongside a team of passionate individuals dedicated to delivering the best and safest entertaining experiences for our customers every day.

We’re looking for bold people who are eager to succeed and ready to level-up the game. If you thrive on innovation, embrace challenges, and want to make a real impact at all levels, FDJ UNITED is your playing field.

Join us in shaping the future of gaming. Are you ready to LEVEL-UP THE GAME?

As a Senior AI Solutions Engineer, you own end-to-end delivery of complex GenAI use cases in production. You remain deeply hands-on (approximately 75–80%) while also shaping solution design, evaluation strategy, and operational readiness.

You take ambiguous business problems and turn them into reliable, secure, and measurable LLM-powered systems on the KAIT platform. This is a senior individual contributor role: you lead through architecture, code, and operational ownership, mentoring others and raising the quality bar without formal people management responsibility.

What you will do

• Own the full lifecycle of GenAI solutions: discovery, technical design, implementation, evaluation, release, and ongoing operation in production.
• Design and build robust LLM-backed services and agentic workflows with explicit tool contracts, safe execution boundaries, retries, and failure handling.
• Lead RAG design for your use cases, including ingestion approach (in partnership with Data Engineering), retrieval tuning, reranking, and systematic evaluation of retrieval and response quality.
• Own production hardening for high-trust capabilities such as Text-to-SQL: schema grounding, golden question sets, safe query enforcement, timeouts, and auditable traces.
• Define and maintain evaluation and release gates for the systems you own, including regression suites and safety checks to prevent silent degradation.
• Ensure strong observability and operability: tracing, metrics, logs, dashboards, alerts, and clear runbooks for supported services.
• Drive cost and performance optimisation for your use cases through model selection, routing, prompt/version control, caching strategies, and token budgets.
• Collaborate closely with Platform Engineering, Data Engineering, and Security to deploy solutions on Kubernetes using approved Helm and Terraform patterns.
• Mentor AI Solutions Engineers through code reviews, design discussions, and pairing on complex problems.
• Communicate technical trade-offs clearly to product and business stakeholders, making risk and impact explicit.
• Operate in line with FDJ UNITED values and applicable governance, risk, and compliance obligations, escalating issues early and documenting decisions.

How you will be measured

• Production outcomes: GenAI solutions delivered and sustained in production with clear ownership and measurable business impact.
• Solution quality: evaluation pass rates and reduction in critical failure modes for owned services.
• Reliability: achievement of defined SLOs and reduced incident recurrence through preventative engineering.
• Cost efficiency: improved and predictable unit economics for owned use cases.
• Security and compliance: strong audit posture and timely remediation of identified risks.
• Team impact: quality of mentorship, reuse of patterns, and reduced rework across the team.

Your experience

• Strong track record shipping and operating LLM-powered applications in production environments.
• Advanced Python and backend engineering skills, with a focus on maintainability and operational excellence.
• Deep practical experience with RAG systems, including vector search, retrieval tuning, and evaluation.
• Strong SQL and analytics fundamentals, including safe access patterns to analytical databases.
• Experience working in cloud-native environments (Docker, Kubernetes) and collaborating with platform/security teams.
• Demonstrated LLMOps discipline: evaluation, monitoring, release gates, and incident follow-up.
• Strong security instincts for GenAI systems, including prompt injection risks and data leakage prevention.
• Ability to lead without formal authority: shape designs, mentor peers, and influence stakeholders.
• Bachelor’s degree in Computer Science, Engineering, or related field, or equivalent professional experience.

We believe talent knows no boundaries. Our hiring process focuses solely on your skills, experience, and potential to contribute to our team. We welcome applicants from all backgrounds and evaluate each candidate based on merit, regardless of personal characteristics as the age, gender, origin, religion, sexual orientation, neurodiversity or disability.