Principal Software Engineer - Machine Learning Platform Engineering

About Riot Games and Role Overview

Founded in 2006 by dedicated gamers, Riot Games focuses on player-centric game creation and is renowned for its flagship title, League of Legends, which has over 100 million monthly players globally. The AI Efficiency team is responsible for creating platforms and tools that help Riot employees leverage AI to streamline workflows effectively and safely. This role plays a key part in scaling and enhancing AI services and developer platforms across the organization.

Key Responsibilities

• Design and enhance internal platforms improving AI service development, deployment, security, and operations.
• Create reusable self-service workflows and platform abstractions to boost developer productivity while maintaining security and governance.
• Enhance platform monitoring, alerting, observability, and deployment safety to increase reliability.
• Define and implement service health metrics such as SLIs and SLOs for informed balancing of reliability and efficiency.
• Develop automation tools to minimize operational workload and accelerate incident detection and resolution.
• Collaborate with engineering teams to embed production readiness and maintainability throughout the software lifecycle.
• Refine CI/CD pipelines and developer workflows to ensure safer and more efficient releases.
• Detect and mitigate risks within distributed systems and infrastructure, promoting long-lasting solutions.
• Troubleshoot AI model serving challenges including compatibility across different hardware and frameworks.
• Conduct resilience testing to identify and address system vulnerabilities prior to user impact.
• Integrate and manage AI-enhanced engineering tools that improve code quality, security, and productivity.
• Develop automation that fuses traditional CI/CD with AI-agent workflows such as automated code reviews and bug remediation.
• Implement safe, auditable deployment of AI agents for tasks including pull request analysis and operational diagnostics.
• Establish governance and escalation protocols for AI-assisted automation to ensure safety and effectiveness.
• Define success criteria and evaluation frameworks for AI-native development tools.
• Lead incident response initiatives and promote systemic improvements for internal platforms.
• Promote operational excellence through comprehensive documentation, standards, and tooling enhancements across the organization.

Required Qualifications

• Bachelor's degree in Computer Science or equivalent experience.
• At least 5 years in platform engineering, SRE, DevOps, developer experience, or similar working with production-grade systems.
• Proficiency in programming and automation in one or more languages like Python, Go, or JavaScript/TypeScript.
• Experience designing or managing internal developer platforms, CI/CD systems, or shared infrastructure.
• Practical experience operating cloud production systems in AWS, GCP, Azure, or similar.
• Deep understanding of observability tools including metrics, logging, tracing, alerting, and dashboarding.
• Expertise in reliability improvements for distributed systems and service-oriented architectures.
• Demonstrated ability in incident management and root cause analysis to facilitate durable fixes.
• Good grasp of containerized environments and orchestration platforms such as Kubernetes or ECS.
• Strong communication skills and ability to collaborate with technical and non-technical partners.

Desired Qualifications

• Familiarity with AI/ML platforms, inference services, and GPU-backed workloads.
• Experience applying SLIs, SLOs, and error budgets for engineering decision-making.
• Platform product mindset focusing on self-service and paved road experiences for internal users.
• Knowledge of infrastructure as code tools such as Terraform or Pulumi.
• Experience with security practices including access control and secrets management in production.
• Capability to balance system availability, latency, cost, and usability at scale.
• Technical leadership experience mentoring engineers and elevating platform reliability standards.
• Experience with AI-assisted engineering tools for code quality, test generation, and automation.
• Understanding of agentic engineering workflows involving AI's integration with CI/CD and browser automation.
• Hands-on experience with end-to-end browser testing frameworks such as Playwright.
• Ability to create governance processes for AI-assisted automation and engineering systems.
• Comfort operating at the convergence of platform, reliability, developer productivity, and emergent AI practices.

Additional Information

This role values expertise in engineering craft, collaboration, and a customer-centric approach toward fellow employees. Prior passion for games is not mandatory.

Benefits

• Comprehensive support for relocation.
• Health insurance coverage for employees and their families.
• Flexible paid time off policy.
• Retirement plans with company match.
• Life insurance, parental leave, and disability coverage.
• A fund to help engage deeper with the player community through gaming.
• Matching donations to non-profit organizations in both time and money.