Site Reliability Engineer – AI Applications (M/W/X)

At Ubisoft, we are reshaping how teams work with information through AI. We build and operate applications for document-rich, interactive, and intelligent use cases, including hybrid search, question answering, document generation, conversational assistants, agentic workflows, and coding assistants.

You will join the team responsible for the reliability, scalability, and operational excellence of the AI platform powering these experiences. This includes the AI Gateway, MCP servers, LLM serving infrastructure, retrieval services, and the surrounding platform components that help teams bring AI applications to production safely.

This role sits at the intersection of fast-moving AI engineering and disciplined site reliability engineering. You will help the platform evolve quickly while ensuring it remains observable, resilient, cost-efficient, and dependable at scale.

Responsibilities

• Operate and improve the reliability, scalability, and performance of the AI platform, including the AI Gateway, MCP servers, LLM serving, retrieval services, and related platform components.
• Define and maintain SLOs, SLIs, and error budgets to guide reliability decisions and balance delivery speed with platform stability.
• Build strong observability across infrastructure, services, and AI-specific signals, such as latency, token throughput, model/provider errors, cost, saturation, and quality indicators.
• Improve the performance, efficiency, and cost profile of model and API serving across cloud, containerized, and high-throughput environments.
• Design graceful degradation, fallback, and failover strategies, including model, provider, and region-level resilience patterns.
• Maintain safe, repeatable deployment practices using GitLab CI/CD, infrastructure as code, automated testing, and progressive delivery where appropriate.
• Lead or contribute to incident response, post-incident reviews, capacity planning, and reliability improvements.
• Partner closely with software engineers, data scientists, ML engineers, security teams, and product stakeholders to productionize AI services responsibly.
• Help establish operational standards, runbooks, dashboards, and best practices for AI application reliability.

Must-Have

• Proven experience in SRE, platform engineering, backend engineering, or infrastructure roles in compute-intensive, data-intensive, or distributed environments.
• Strong understanding of reliability engineering practices, including SLOs, error budgets, observability, capacity planning, incident management, and post-incident analysis.
• Strong programming skills in Python and practical experience with Rust, or a willingness to work deeply with Rust-based services.
• Hands-on experience with cloud platforms, Docker, Kubernetes, and production-grade service operations.