Senior Site Reliability Engineer in Vancouver

The SRE team within the Platform & Infrastructure department at Walt Disney Animation Studios (WDAS) focuses on optimizing service deployments and improving system availability, latency, performance, and observability. We build performant infrastructure that artists use daily to create our celebrated animated content.

The Senior Site Reliability Engineer will drive the design, implementation, and operation of reliable, scalable infrastructure across the studio. This role partners closely with team members and stakeholders to evaluate emerging technologies, translate requirements into production-ready solutions, and ensure operational excellence through automation, observability, and reliability engineering practices.

Responsibilities:

• Design, implement, and support robust on-premises and cloud-native deployments using infrastructure-as-code, security automation, and continuous improvement, while maintaining high reliability standards through comprehensive observability, SLIs/SLOs, and performance optimization.
• Securely deploy, operate, and support AI-powered tools and ML infrastructure within a production environment.
• Collaborate with stakeholders throughout the studio to understand workflows and translate business requirements into end-to-end platform and infrastructure solutions.
• Contribute to the design, operation, and evolution of SRE managed technologies, including CI/CD platforms, Git source management, cloud hosting, containerization, and web technologies such as Apache HTTPd and NGINX.
• Develop meaningful telemetry, alerting, and operational runbooks to maximize service visibility and minimize mean time to repair (MTTR).
• Evaluate emerging technologies and operationalize new functionality by creating documented standards and reusable patterns to encourage adoption.
• Build internal tooling to enable the SRE team to efficiently isolate, diagnose, and resolve platform, service, and application issues.

Key Qualifications:

• BS in Computer Science, Computer Engineering, Electrical Engineering, or comparable field of study, and/or equivalent work experience.
• 5+ years of experience in SRE, DevOps, technical operations, systems engineering, software engineering, and/or related disciplines.
• Expertise in distributed systems, networking, hardware architecture, and capacity planning.
• Proven ability to lead and collaborate on large-scale cross-team projects with strong verbal and written communication skills.
• Proficiency in UNIX/Linux administration, troubleshooting, performance tuning, and security.
• Experience with monitoring and observability tools such as Datadog, Prometheus, and Grafana, including AI-specific metrics such as model benchmarking, inference latency, and token consumption.
• Proficient with containerization and orchestration systems in enterprise production environments (e.g., Docker, Podman, Kubernetes, Rancher, AWS ECS and EKS).
• Experience with configuration management and infrastructure as code (e.g., Terraform, Helm, CloudFormation, Puppet, and Ansible).
• Experience implementing enterprise MLOps infrastructure that enables validation, deployment, fallback, multi-model routing, load balancing, quota management, inference metrics, and provider abstraction (leveraging technologies such as AWS Bedrock, JFrog Artifactory, and LiteLLM).
• Experience with continuous integration tools (e.g., Jenkins, Gitlab CI/CD, AWS CodeBuild, CodeDeploy, Spinnaker).
• Expertise in architecting, deploying, and maintaining scalable solutions within cloud environments (e.g., AWS, GCP, Azure).
• Experience with secrets management and data protection (e.g., HashiCorp Vault).
• Proficient in one or more languages such as Python, Java, Scala, Go, Rust, or Ruby.

Bonus Qualifications:

• Experience within a Film Production environment.
• Experience in web server administration.
• Knowledge of securing MLOps deployments through implementing LLM and MCP gateways and security scanning (e.g., JFrog Xray).
• Knowledge of setting up and maintaining cloud/on-prem runtime environments for AI agents (e.g., AWS Bedrock AgentCore, Google Vertex AI Agent Engine, Temporal).
• Knowledge of provisioning, monitoring, and maintaining GPU infrastructure (e.g., NVIDIA GPUs, CUDA, cuDNN, NVML), including GPU virtualization and partitioning (e.g., NVIDIA MIG), and optimizing utilization for inference workloads.
• Knowledge of model serving and inference frameworks (e.g., vLLM, SGLang, Ray Serve, Ollama / llama.cpp) with foundational knowledge of how LLMs are loaded and executed.

The Walt Disney Company is an Equal Opportunity Employer.

PAY TRANSPARENCY: The hiring range for this position in British Columbia, Canada is C$120,700 to C$161,800 per year. The base pay actually offered will take into account internal equity and also may vary depending on the candidate’s geographic region, job-related knowledge, skills, and experience among other factors. A full range of medical, financial, and/or other variable pay or benefits, may be offered dependent on the level and position offered.