Distributed Computing Platform Engineering Lead

Oreol seeks a Distributed Computing Platform Engineering Lead to design and manage the operational foundations of its next-generation distributed computing platforms in a remote-friendly role based in Luzern.

As an ETH Zurich spin-off candidate, Oreol is developing advanced distributed computing systems that place accelerated processing closer to data sources. The company is hiring a Platform Engineering Lead to establish and refine the operational backbone of these platforms, defining how compute environments are deployed, managed, and utilized across customer-owned and regional infrastructures.

Responsibilities

• Architect and enhance the software platform responsible for deploying and running distributed computing environments.
• Create automation frameworks to ensure reproducible deployment, configuration, and lifecycle management of infrastructure.
• Establish engineering standards, workflows, and operational best practices across diverse environments.
• Construct and sustain provisioning pipelines for both physical and virtual systems.
• Ensure platform reliability, observability, and operational excellence throughout the entire technology stack.
• Partner with software, hardware, and product teams to integrate new technologies into the platform.
• Assess and implement tools that boost 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 promote engineering best practices within the organization.
• Collaborate closely with customers and partners during platform deployments and technical integrations.

Requirements

• Degree in Computer Science, Computer Engineering, Information Technology, or a related technical field.
• 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.

What the company offers

• 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.

About the company

Oreol is an ETH Zurich spin-off candidate operating in a fast-moving startup environment. The company focuses on developing next-generation distributed computing platforms that bring accelerated computing closer to where data is created and used.

• Early-stage startup environment with significant ownership and autonomy.
• Collaboration with experienced researchers and engineers.
• Focus on cutting-edge computing technologies and heterogeneous platforms.
• Support for continuous learning and professional development.