The Opportunity
Provide technical leadership for Scientific Computing platform operations, complex L3 escalations, selected L2 support, and continuous improvement, while helping establish scalable support practices, runbooks, escalation paths, operational readiness, and knowledge transfer.
Build automation, tooling, observability, monitoring, and alerting capabilities that reduce operational toil and improve platform reliability, supportability, maintainability, and service health.
Provide technical leadership for AWS, on-premises, and hybrid compute, storage, networking, and platform services, including upgrades, migrations, lifecycle activities, and integration of scientific applications and services.
Participate in incide nt response and root cause analysis, ensuring lessons learned translate into durable platforms and operational improvements.
Support data lifecycle, access, identity, and integration requirements across Scientific Computing services.
Partner closely with Engineering and other technical teams to ensure new capabilities are operationally ready and supportable, while providing technical direction, mentoring, and work coordination for junior engineers and contractors.
Who You Are
Bachelor’s or Master's degree in computer science, engineering, computational science, a related field, or equivalent experience. Typically 4-7 years of relevant professional experience with a bachelor’s degree, with equivalent experience considered for advanced degrees or comparable practical experience.
Experience supporting infrastructure and platforms across cloud and on-premises environments, with strong experience in Amazon Web Services and a strong understanding of Linux systems, networking, storage, compute, distributed systems, and cloud infrastructure concepts.
Experience providing technical leadership for complex production platforms or infrastructure services, including leading technical discussions, establishing operational practices, and coordinating work across multiple contributors.
Software development or scripting experience using languages such as Python, Go, or Bash, together with infrastructure-as-code, configuration management, and machine image automation technologies such as Terraform, Terragrunt, AWS CloudFormation, Ansible, and Packer. Demonstrated ability to effectively use AI-assisted engineering tools and adapt to emerging AI and agent-based workflows.
Experience with containers and orchestration technologies such as Docker, Kubernetes, and Helm, as well as CI/CD and GitOps practices using technologies such as GitLab CI/CD, ArgoCD, or similar.
Experience with monitoring and observability technologies such as Grafana, Prometheus, Loki, or similar, including troubleshooting complex production issues, leading incident and root cause analysis activities, and translating recurring operational issues into automation, platform improvements, documentation, or engineering requirements.
Ability to collaborate effectively across engineering, infrastructure, security, support, and scientific teams.
Experience with High Performance Computing (HPC) or other large-scale shared compute environments, including familiarity with workload schedulers such as Slurm and cloud-based HPC platforms such as AWS ParallelCluster is preferred.
Experience supporting scientific applications, research computing, GPU, or AI/ML workloads is preferred.
Who we are
A healthier future drives us to innovate. Together, more than 100’000 employees across the globe are dedicated to advance science, ensuring everyone has access to healthcare today and for generations to come. Our efforts result in more than 26 million people treated with our medicines and over 30 billion tests conducted using our Diagnostics products. We empower each other to explore new possibilities, foster creativity, and keep our ambitions high, so we can deliver life-changing healthcare solutions that make a global impact.
Let’s build a healthier future, together.
Roche is an Equal Opportunity Employer.
