AI Engineer (Infrastructure Team)
Xsolla is a video game commerce company that provides a suite of tools and services—including merchant of record payment processing, tax management, fraud prevention, compliance, refunds, dispute management, and end-user support—to help game developers and publishers launch, grow, and monetize their games globally. It serves video game developers, publishers, and studios of all sizes across global and regional markets.
About Xsolla
Xsolla connects the tools, systems, payments, and web shops used by the video games industry, positioning itself as a global merchant of record supporting over 1,000 payment methods and a cumulative audience of 50 million, with transaction fees around 5%. Its services include tax management, fraud monitoring and prevention, global and regional regulatory compliance, refund and dispute management, and end-user payment support. Xsolla's product lineup includes the Xsolla SDK for native in-app payments on side-loaded apps and alternative app stores, a Buy Button enabling link-out purchases from iOS mobile games in the U.S., and Web Shop for building customized, direct-to-consumer game storefronts. The company works with major gaming industry partners and clients such as Mytona, Ubisoft, MARVEL SNAP, and others, and highlights partner success stories, industry events, and its own culture and hiring initiatives on its site.
Skills
About the Role
You will help build and operate the intelligent systems that power Xsolla's infrastructure. As part of the Infrastructure Team, you will implement AI-driven solutions across cloud optimization, security, automation, and developer support — helping shift from manual and reactive operations to predictive, self-optimizing infrastructure management. You'll work with LLMs, ML pipelines, and AI automation frameworks, applying them to real operational problems at scale, while experimenting, iterating, and delivering in a fast-moving environment.
Requirements
- 5–7 years of experience in infrastructure engineering, DevOps, SRE, or a related field
- Hands-on experience with GCP (priority) and/or AWS; solid understanding of cloud resource management, scaling, and cost structures
- Practical experience building or integrating AI/ML-powered tools in an operational context (anomaly detection, predictive models, LLM-based automation, or similar)
- Experience with infrastructure-as-code tools — Terraform, Puppet, Ansible, or equivalent
- Proficiency in Python for scripting, automation, and AI/ML integration; Bash or Go a plus
- Working knowledge of Kubernetes and container orchestration in production environments
- Familiarity with observability and monitoring stacks (Prometheus, Grafana, ELK, Datadog, or similar)
- Familiarity with LLM APIs (OpenAI, Anthropic, or similar) and prompt engineering for operational use cases
- Strong problem-solving mindset with a bias toward automation and eliminating toil
- Fluent in English (written and verbal)
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 (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