About Neurophos

The demand for new data centers and AI compute is rapidly outpacing the planet's energy capacity. Digital solutions are hitting a power wall as we approach the physical limits of traditional silicon. Conquering this bottleneck means rethinking the fundamental architecture of inference compute. The industry's current path can't meet the need, so we're taking a different approach.

Instead of traditional electronic circuits, we use silicon photonics and an active, programmable metasurface to perform matrix multiplications at the speed of light. Our optical cells are 10,000x smaller than traditional photonic components, enabling unprecedented density. By using photonics instead of electricity, our chips become more efficient as they scale. This architecture will deliver up to 100 times the energy efficiency of existing solutions while significantly improving performance for large-scale AI inference.

We’ve assembled a world-class team of industry veterans and recently raised a $110M Series A led by Gates Frontier. Participants include M12 (Microsoft’s Venture Fund), Carbon Direct Capital, Aramco Ventures, Bosch Ventures, Tectonic Ventures, Space Capital, and others.

Join us and shape the future of computing!

Location: Austin, TX. Full-time on-site position.

Reports To: Director of Technical Program Management

FLSA Status: Exempt

Position Overview

The Electronic IC (EIC) is the high-speed mixed-signal ASIC at the heart of our optical compute engine. It drives, reads out, and controls our photonic hardware and connects it to the rest of the system. We are looking for an experienced hardware TPM to drive the EIC program end-to-end: from architecture convergence with our chip architects, through design, verification, physical design, and tapeout at a leading-edge foundry, into post-silicon bring-up and system integration.

You will be the connective tissue between the architecture team, digital/analog/mixed-signal design, DV, physical design, packaging, photonics, and platform hardware — and the single source of truth for EIC schedule, risk, and readiness. This is a first-silicon program at a fast-moving startup: you will define the process where none exists, and you'll be judged on working silicon.

We develop silicon the AI-first way. AI agents and LLM tooling are embedded in how we write specs, track requirements, generate and review code, close verification, and run the program itself. You'll drive it: building an AI-augmented program machine.

Key Responsibilities

Drive the end-to-end EIC program: integrated schedule, milestones, dependency map, staffing outlook, and risk register from architecture through tapeout, bring-up, and production readiness.

Champion the AI-first development flow: deploy AI/LLM tooling across spec and requirements management, schedule and dependency tracking, risk registers, status reporting, and documentation.

Partner with the architecture team to converge the EIC specification. Drive spec and design reviews, decision logs, freeze criteria, and change control to ensure downstream execution starts from a stable baseline.

Drive execution across RTL, DV, analog/mixed-signal, DFT, and physical design teams, and coordinate external partners: IP vendors, EDA vendors, design services, foundry, and OSAT.

Partner with design and DV leads to adopt AI-assisted design, verification, and debug-triage flows where they cut schedule without compromising signoff quality.

Build and drive the tapeout readiness checklist: verification closure, timing/physical/electrical signoff, DRC/LVS, mask release. Run the tapeout decision process with engineering leadership.

Manage the foundry engagement day-to-day: shuttle and full-mask schedules, PDK/deck updates, wafer starts, and delivery tracking.

Drive post-tapeout execution: bring-up plan and lab readiness, package/assembly and OSAT coordination, ATE and bench test planning, silicon debug triage, errata tracking, and respin scoping if needed.

Track cross-domain dependencies between the EIC and photonic IC, package/substrate, board, firmware, and software teams; surface risks early and drive mitigation to closure.