Scientific Computer Engineer

Revolution Medicines is a global, commercial-state oncology company dedicated to discovering, developing and delivering innovative medicines for patients with RAS-addicted cancers. Leveraging its differentiated RAS(ON) tri-complex inhibitor platform, the company is advancing a broad, integrated portfolio of oral RAS(ON) inhibitors designed to directly target the active, cancer-driving state of RAS. Founded on rigorous scientific inquiry and a willingness to challenge long-held assumptions, Revolution Medicines is committed to changing the trajectory of disease for patients with RAS-addicted cancers worldwide.

Our people are united by a shared way of working: follow the science, challenge assumptions, act with urgency and hold ourselves to a high standard of rigor—all in service of patients.

The Opportunity:

We are seeking a Staff Cloud Infrastructure / Scientific Computer Engineer to help build, operate, and improve the infrastructure foundations that support computational science, data engineering, analytics, and enterprise business operations across RevMed. This role will emphasize site reliability engineering, Kubernetes operations, observability, Databricks infrastructure, and cloud financial management (FinOps).

This role will partner with scientific, G&A, data, security, and IT stakeholders to deliver reliable, secure, scalable compute and platform services. The ideal candidate brings deep infrastructure experience, strong operational judgment, and the ability to translate scientific and business computing needs into practical, reusable platform patterns. They will balance reliability, performance, security, and cost, using operational data to guide improvements.

• Design, operate, and improve secure cloud infrastructure for R&D and scientific computing workloads.

• Build reusable infrastructure patterns for compute, storage, networking, identity, secrets management, and observability.

• Use Infrastructure as Code, primarily Terraform, to standardize provisioning and change management.

• Apply SRE practices to critical platform services, including service-level indicators and objectives, actionable alerting, incident response, post-incident reviews, and automation that reduces operational toil.

• Operate and improve Kubernetes environments, including cluster upgrades, workload deployment, resource allocation, autoscaling, networking, access controls, and troubleshooting.

• Develop observability across cloud, Kubernetes, and data platforms using metrics, logs, and traces to identify failures, diagnose performance issues, and understand capacity needs.