Director - Embedded Systems

Quantum Source is building a fault-tolerant, compound photon-atom quantum computer. We're a young, multidisciplinary team combining quantum physics, optics, mechanical engineering, hardware, firmware, and software.

Getting to fault tolerance and beyond requires classical compute infrastructure operating at a scale most engineering organizations never confront: real-time control loops synchronized across enormous numbers of physical qubits, error correction decoding running against microsecond latency budgets, and orchestration layers that will eventually bridge into HPC to run useful quantum algorithms.

We're looking for an Engineering Manager to build an organization that carries our system through scale-up — recruiting and building out the group, setting the technical roadmap for control, real-time error correction, and orchestration, and designing the architecture and HPC interfaces the machine will need as it grows from tens of qubits to orders of magnitude beyond.

This is as much an organization-building role as an engineering one. You'll hire and grow teams across FPGA/embedded, real-time software, and distributed systems, while staying technical enough to make architecture calls yourself in the near term.

Responsibilities

• Recruit, build, and lead a multidisciplinary organization spanning FPGA, embedded firmware, real-time software, and distributed systems engineering — growing today's hardware/software team into the org that will support a fault-tolerant, large-scale quantum computer.
• Own the technical roadmap and architecture for the classical compute stack: real-time control today, scaling toward large-scale orchestration and real-time quantum error correction decoding, and interfaces to HPC systems.
• Design for scale from day one: define the architecture, staffing plan, and technology choices that let the control and compute stack grow by orders of magnitude without a rewrite.
• Drive technical decisions, architecture and design reviews, and system integration across FPGA, hardware, firmware, and software.
• Partner closely with Experimental Physics, Optics, Mechanical Engineering, System Architecture, and Theory teams — translating across disciplines and keeping the compute roadmap aligned with how the physical system evolves.
• Manage technical engagements with external vendors and subcontractors.
• Ensure high-quality execution, predictable delivery, and engineering excellence as both the team and the system scale.

Requirements

• B.Sc. or M.Sc. in Electrical Engineering, Computer Engineering, Computer Science, or a related field.
• 10+ years developing complex real-time systems.
• 5+ years of engineering management experience, including recruiting and leading teams across more than one engineering discipline (e.g., hardware/firmware and software).
• Hands-on FPGA development experience (RTL design, integration, and debugging).
• Strong background in digital hardware, embedded firmware, and system integration.
• Software or systems architecture experience with distributed or large-scale compute systems.
• Direct experience scaling a system and/or an organization.
• Demonstrated ability to operate across disciplines: comfortable moving between hardware, firmware, and software conversations, and quick to build technical fluency in adjacent domains.
• Proven experience leading multidisciplinary R&D projects with structured planning and milestone-driven execution.
• Experience managing external vendors, subcontractors, or supply partners on technical programs.
• Excellent leadership, communication, and organizational skills, with the ability to recruit and sell a technical vision to candidates in a competitive market.

Advantages

• Background in physics, optics, mechanical engineering, or similar hard-science or engineering field.
• Experience with electro-optical, photonics, or quantum systems.
• Experience with Xilinx/AMD FPGA platforms.
• Experience with real-time decoding algorithms (e.g., Union-Find, MWPM, or neural-network decoders) or other latency-critical compute pipelines.
• Experience with distributed systems or HPC orchestration at scale.
• Background in latency-critical or mission-critical domains.
• Experience bringing complex products from development to manufacturing.