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
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)
Nice to Have
- Experience with AI workflow orchestration frameworks (LangChain, LlamaIndex, n8n, or similar)
- Exposure to AIOps platforms (Dynatrace, Datadog AI, Moogsoft, BigPanda, or similar)
- Background in FinOps or AI-driven cloud cost optimization
- Familiarity with vector databases (Weaviate, Pinecone, Qdrant) for knowledge retrieval systems
- Experience with VMware or hybrid cloud environments
- GCP and/or AWS cloud certifications
- Prior experience in gaming, high-growth tech, or SaaS platform environments
Benefits
- Unlimited Flexible Time Off
- Personalized career roadmap for each employee
- Professional development through training and educational opportunities
Additional Information
- The duties and responsibilities of this position may evolve over time to support the organization's goals and individual growth
- By submitting your application, you consent to Xsolla conducting background checks, where permitted by law, after the final interview stage. All checks will comply with local regulations, and your information will be handled confidentially.
- Xsolla takes your privacy seriously and will not sell or externally distribute any personal data received during the hiring process. In accordance with applicable data protection laws, Xsolla is committed to protecting your personal information and respecting your privacy. For any inquiries related to data privacy, please contact: careers@xsolla.com
