Optical Engineer

Exowatt is revolutionizing the energy landscape for the AI era with our groundbreaking P3 system that captures solar energy, stores it as heat, and generates electricity on demand. Founded in 2023 and backed by leading investors including Andreessen Horowitz, Sam Altman, and Felicis, we're committed to providing clean, modular, and scalable power that meets the rapidly growing demands of AI infrastructure. Our mission is to make sustainable renewable energy always available and almost free, enabling technological advancement while protecting our planet.

We are seeking a highly skilled and motivated Lead Optical Engineer to own concentrator design, optical testing, and model validation for the P3. In this role, you will design and optimize non-imaging optics for maximum flux transfer, build and automate optical test setups, validate models against on-sun performance, and work across the optic-to-thermal boundary that defines the P3 architecture. You will collaborate closely with the Optical Product Development, R&D, and thermal teams to ensure alignment between design intent, test outcomes, and delivered system performance.

Non-imaging concentrating optics experience is required for this role.

This position is based in Austin, TX preferred, however an alternate location of Miami, FL is possible for the right candidate. If hired for this role, relocation to one of these sites is required. We provide relocation assistance.

What You'll Do:

• Design and optimize non-imaging concentrating optics — Fresnel primaries and secondary optical elements — to maximize flux transfer, uniformity, and intercept factor rather than image quality.

• Build an optical error budget that rolls slope error, tracking error, and alignment tolerances into an intercept-factor model, and validate it against hardware.

• Design for uniform irradiance on the receiver, mitigating hot spots and the material stress that uneven flux drives on a thermal absorber.

• Design, automate, and optimize optical test setups for our concentrators and complex opto-mechanical assemblies, ensuring efficiency and precision.

• Characterize concentration ratio, acceptance angle, focal-spot flux distribution, and end-to-end optical efficiency, and validate these against Monte Carlo ray-tracing models.

• Automate ray-tracing, test procedures, and analysis using Python (and C++/MATLAB as needed) to streamline workflows and improve accuracy.

• Conduct on-sun testing — flux mapping, calorimetry, and pyrheliometer-based efficiency measurement — and reconcile field results with simulation.

• Feed validated optical performance into annual optical-efficiency models, thermal models, and the system digital twin (developed with NVIDIA and AWS).