Staff ML Infrastructure Engineer

About the Role

The Staff ML Infrastructure Engineer will be responsible for designing, implementing, and maintaining AI/ML-powered solutions across Xsolla's infrastructure. This role involves enhancing operational efficiency, security, and developer experience through advanced automation and intelligent systems.

Responsibilities

• Design and implement AI/ML-powered solutions for infrastructure use cases, including predictive autoscaling, anomaly detection, intelligent cost optimization, and automated remediation across GCP and multi-cloud environments.
• Build and maintain AI-driven monitoring and observability systems that correlate logs, metrics, and traces to surface root causes, predict bottlenecks, and reduce mean time to resolution (MTTR).
• Develop and operate automated incident response workflows using AI-powered playbooks that diagnose, contain, and resolve infrastructure issues with minimal manual intervention.
• Integrate AI tooling into CI/CD pipelines to improve deployment reliability, automate test prediction, score release health, and support rollback automation.
• Contribute to the development of internal AI agents and virtual assistants integrated into developer workflows (e.g., Slack, IDEs, Confluence) — enabling self-service for provisioning, troubleshooting, and infrastructure guidance.
• Implement AI/ML-based anomaly detection and automated vulnerability management workflows to enhance the security posture of Xsolla's infrastructure.
• Prototype and productionize Generative AI solutions for infrastructure automation, including auto-generation of Terraform/Puppet modules, IaC configurations, runbooks, and change documentation.
• Collaborate with senior engineers and leadership to evolve and execute the infrastructure AI strategy across its implementation phases.
• Maintain clear documentation of AI tools, integrations, and automated workflows; share knowledge and best practices across the team.