Distributed Computing Platform Engineering Lead

Oreol is an ETH Zurich spin-off candidate developing next-generation distributed computing platforms that bring accelerated computing closer to where data is created and used. Our systems combine modern software platforms, heterogeneous hardware, and edge-to-core deployment models to enable advanced AI and scientific workloads.

We are looking for a Platform Engineering Lead to help build and evolve the operational foundations of our distributed platforms. In this role, you will shape how compute environments are deployed, managed, and consumed across a growing portfolio of customer-owned and regional infrastructures.

• Design and evolve the software platform used to deploy and operate distributed computing environments.
• Develop automation frameworks that enable reproducible deployment, configuration, and lifecycle management of infrastructure and services.
• Define engineering standards, workflows, and operational practices across multiple environments.
• Build and maintain provisioning pipelines for physical and virtual systems.
• Drive platform reliability, observability, and operational excellence across the entire stack.
• Collaborate with software, hardware, and product teams to integrate new technologies into the platform.
• Evaluate and introduce tooling that improves scalability, developer productivity, and operational efficiency.
• Contribute to reference architectures for distributed and heterogeneous computing systems.
• Lead technical investigations, proof-of-concepts, and platform validation activities.
• Mentor engineers and foster engineering best practices within the organization.
• Work closely with customers and partners during platform deployments and technical integrations.

• Degree in Computer Science, Computer Engineering, Information Technology, or a related technical discipline.
• Several years of experience designing and operating production infrastructure or platform environments.
• Strong Linux systems engineering background.
• Hands-on experience with automation and Infrastructure as Code tools (Ansible, Terraform, or similar).
• Experience building and maintaining CI/CD pipelines and automated operational workflows.
• Familiarity with containerized environments and orchestration technologies such as Kubernetes.
• Solid understanding of networking, distributed systems, and infrastructure security principles.
• Experience operating physical or hybrid infrastructure environments.
• Ability to troubleshoot complex cross-layer issues spanning hardware, operating systems, networking, and applications.
• Strong communication skills and the ability to collaborate across multidisciplinary teams.
• Comfortable working in a fast-moving startup environment.

Nice to have

• Experience with high-performance computing, AI infrastructure, or accelerated computing platforms.
• Familiarity with GPUs, FPGAs, or other specialized compute architectures.
• Experience with edge computing or distributed systems.
• Exposure to data center operations, infrastructure monitoring, or hardware integration.
• Cloud certifications or experience with public cloud environments.

• Join an early-stage ETH Zurich spin-off candidate and help shape the company’s technical foundations.
• Significant ownership and autonomy from day one.
• Opportunity to work on cutting-edge computing technologies and heterogeneous platforms.
• Flexible and remote-friendly working environment.
• Competitive salary and participation in the company’s long-term success.
• Work alongside experienced researchers and engineers at the intersection of infrastructure, AI, and systems engineering.
• Modern equipment and support for continuous learning and professional development.

If you enjoy building robust platforms, solving complex systems challenges, and creating the operational backbone for next-generation computing environments, we would love to hear from you.

Our hiring process typically consists of an introductory conversation, a technical discussion with the engineering team, and a final interview focused on mutual fit and long-term vision.