Principal DevOps & SRE — AI Efficiency Platform Lead

Riot Games

Singapore

On-site

SGD 180,000 - 280,000

Full time

14 days+

Get more replies from employers

Send a job-specific resume in minutes.

Benefits offered by this job

Full relocation support

Comprehensive health insurance

Open paid time off

Retirement benefits with company match

Life insurance and parental leave

Job summary

Riot Games is seeking a Principal DevOps / Site Reliability Engineer for the AI Efficiency team in Singapore. The role focuses on building and operating scalable AI-enabled platforms, improving observability, and reducing operational toil.

You will collaborate with software engineers, data scientists, and security teams to ensure production readiness and reliability. You will lead incident responses, define SLOs/SLIs, and champion governance for automated operational systems while mentoring

Qualifications

Bachelor’s degree in Computer Science or a related field or equivalent professional experience.
5+ years in SRE, DevOps, or equivalent roles supporting production systems.
Strong programming and automation skills in Python, Go, JavaScript, or TypeScript.
Experience designing and operating cloud-based production systems in AWS, GCP, Azure, or similar.
Experience building and maintaining CI/CD pipelines and deployment automation.
Strong observability, metrics, logging, tracing, dashboards, and alert design.
Experience incident response, on-call support, root-cause analysis, and post-incident improvements.
Experience improving reliability, availability, scalability, and performance of distributed systems.
Strong knowledge of containers and orchestration (Kubernetes, Docker, etc.).
Experience with infrastructure-as-code tools (Terraform, Pulumi, CloudFormation).
Linux, networking, DNS, load balancing, authentication, secrets management, and cloud security fundamentals.
Ability to drive improvements across teams and collaborate across organizational boundaries.
Experience mentoring engineers and establishing engineering standards.

Responsibilities

Own and improve reliability, availability, scalability, performance, and health of the AI Efficiency platform and tools.
Design, build, and maintain infrastructure, deployment systems, and operational foundations for production AI services.
Improve CI/CD pipelines, release engineering, environment management, and deployment automation.
Set production-readiness standards with monitoring, ownership, and rollback strategies.
Define and operationalize SLOs, SLIs, and reliability metrics to guide priorities.
Build observability across applications, infrastructure, and service dependencies.
Establish on-call practices, escalation paths, and runbooks for production.
Lead diagnosis and resolution of incidents, with blameless post-incident reviews.
Build automation to reduce toil and improve MTTR.
Implement safe deployment patterns: canary, feature flags, health checks.
Perform capacity planning, load testing, and performance analysis for AI services.
Design backup, recovery, failover, and disaster-recovery strategies.
Identify single points of failure and systemic risks across systems.
Improve developer experience with self-service workflows and reusable infrastructure.
Maintain infrastructure-as-code, secrets-management, and environment governance.