Lead Network and Product Systems Engineer

We are building the optical layer that the next generation of AI and quantum infrastructure will run on. Our first product is an optical circuit switch for AI data centers. As Lead Network and Product Systems Engineer, you will define where and how our switch creates value in real networks. You will validate deployment and endpoint assumptions, write the product requirements, and own the end-to-end tests that prove the switch works with real traffic. You will work closely with the founders on customers and design partners. If you have built production networks and want to shape a new kind of hardware, you'll fit well here.

• Use cases. Choose priority deployment scenarios with the founders. Define endpoints, topology, workloads and buyer constraints.
• Product requirements. Write and own the product requirements document and the prioritized technical backlog.
• Endpoint compatibility. Lead the review of transceivers and link budgets: wavelength, power, reflection, FEC and receiver recovery.
• Control interface. Define the control and API contract: valid mappings, rollback, fault containment and restart.
• End-to-end testing. Design and run experiments against a matched baseline. Measure recovery time, errors and workload completion.
• Partners. Build the technical acceptance plan with design partners and recruit transceiver or system partners where needed.
• AI in the workflow. Use AI tools for analysis, simulation and documentation.
• Cross-team work. Work with optics, electronics and the founders so the product stays tied to what customers need.

• Degree in computer science, electrical engineering, physics or a related field. MSc or PhD preferred.
• Hands-on ownership of production data-center networks or optical-network prototypes.
• Deep understanding of data-center architecture, topology and traffic control.
• Working knowledge of optical transceivers and link budgets.
• Hands-on performance measurement and debugging on real systems.
• Strong product judgment and the ability to challenge incompatible requirements.
• Clear written and verbal communication, fluent English.
• Comfortable using AI tools across the workflow.

• Optical circuit switching in production or research.
• GPU cluster networking (RoCE, InfiniBand, rail-optimized fabrics).
• FPGA or NIC-level timing and synchronization.
• Experience working with hyperscaler or AI-infrastructure customers.
• Startup experience.

• Competitive salary commensurate with experience.
• Equity and benefits available, to be agreed upon.