Job Description
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.
Key Responsibilities
- Own optical test stands end to end, from indoor characterization benches to the high-flux test facility to outdoor on-sun stands: concept, CAD, fixtures, instrumentation, commissioning, first light, and day-to-day operation
- Design and run test campaigns from hypothesis to conclusion: write the test plan, build the setup, take the data, quantify the uncertainty, and present results that drive real design decisions
- Characterize optical components and assemblies: alignment verification, focal and flux measurements, camera-based flux mapping, radiometry and thermal power measurement, reflectance and transmittance
- Develop precision alignment procedures and tooling for optical assemblies on tracker platforms, and verify pointing and tracking accuracy in the field
- Select, mount, wire, and calibrate instrumentation (radiometers and power sensors, thermocouples, cameras, tilt sensors, encoders, weather and irradiance instruments) and integrate everything into DAQ systems
- Automate tests in Python: instrument control, data acquisition, analysis pipelines, and the plots and reports that make results legible to the whole team
- Make the test infrastructure agent-ready: expose instruments, test sequencing, and data pipelines through clean scriptable interfaces so AI agents can configure a test, run it, watch it overnight, and flag anomalies, then use those agents to run campaigns that would otherwise wait on a human
- Close the loop between simulation and hardware: compare measured optical performance against raytrace predictions and chase discrepancies to root cause, whether the flaw is in the hardware or in the measurement
- Run environmental and durability testing on optical components (thermal cycling, weathering, soiling) and help build the reliability story for hardware that must survive decades outdoors
- Own test safety around concentrated flux: hazard analyses, interlocks, PPE, and safe operating procedures for indoor high-flux testing and on-sun operations
- Document test plans, procedures, results, and decisions on the team wiki; present and defend your own work in design reviews, growing into ownership of the team's test strategy over time
Requirements
- BS or MS in Optical Engineering, Mechanical Engineering, Electrical Engineering, Aerospace Engineering, Physics, or a closely related discipline
- 2+ years of hands-on laboratory, test, or integration experience with optical or precision hardware; graduate research and substantial internship work count
- Strong fundamentals in math and physics: you reason from first principles, estimate before you compute, and check every result against known limits before you believe it; we probe this hard in interviews
- Hands-on experience on an optical bench: mounting, aligning, and characterizing optics, and the care and cleanliness habits that precision components demand
- Instrumentation fundamentals: sensor selection, signal conditioning, calibration, and DAQ integration
- Python for test automation and data analysis: instrument control, numpy/pandas data reduction, publication-quality plots
- Fluency with AI coding agents (Claude Code, Codex, or similar) as a daily engineering tool: you use them to write most of your code, and you own every line they produce, reviewed, tested, and understood; expect us to ask you to show how you work with AI the same way we ask about your bench skills
- The instinct to make work agentic: you can decompose a workflow into steps an agent can execute, with clean interfaces, verifiable checkpoints, and guardrails, and you have the judgment to catch an agent when it is confidently wrong; engineers who can direct several agents at once will outrun those who type everything themselves, and we hire the former
- Working knowledge of a parametric CAD tool for fixtures and test hardware; the team uses PTC Creo and SolidWorks
- The discipline of good measurement: you control variables, calibrate before you trust, quantify uncertainty, and distrust your own data until the measurement itself is validated
- A track record of building real test setups or hardware: research labs, internships, capstone projects, FSAE, solar car teams, robotics, or independent builds all count; bench experience matters more than coursework grades
- The drive to own the full cycle yourself: take a question to a test plan, to a built stand, to trustworthy data, learn from the mistakes, and iterate quickly rather than handing steps off to others
- Comfort with both bench and field work: precision optical alignment in the morning, commissioning an outdoor test stand in the Miami sun in the afternoon
- Structured root-cause instincts when results look wrong: the first suspect is always the measurement, and you know how to clear or convict it
- Strong written communication: your test reports should let the next engineer reproduce the measurement without asking you
- The temperament to hold your ideas loosely: designs evolve weekly and priorities shift on real evidence; engineers who can let go and update move fastest
- Radiometry or photometry experience: power meters, flux mapping, camera-based flux measurement, IR thermography
- Exposure to concentrating optics, heliostat or CPV testing, or high-flux measurement
- Camera-based metrology and image processing: OpenCV or similar, converting images into calibrated measurements
- Thermal measurement experience: calorimetry, heat flux sensors, flow-and-temperature-based power measurement
- Design validation and reliability practices: DVP&R, accelerated aging, or environmental qualification against IEC/ASTM standards for solar hardware
- Motion control experience: stages, encoders, motorized mounts, closed-loop pointing systems
- Exposure to optical simulation (LightTools, Zemax, or another raytracer) and to comparing measurement against model
- Statistics for test engineering: design of experiments, measurement system analysis, formal uncertainty budgets
- Experience building agentic systems around real hardware or simulation: agents driving instruments or ray-trace models through tool interfaces (MCP or similar), running parameter sweeps overnight, and summarizing the results; or any project where you gave an AI real levers and made its output trustworthy
- Machine shop skills and rapid prototyping: you can make the bracket you need instead of waiting for it
- Interest in solar energy, heliostats, or large-scale renewable infrastructure
- Willingness to work extended hours and occasional weekends when test campaigns, commissioning windows, or program deadlines demand it
- Ability to lift up to 25 lbs unassisted, and to work on ladders and lifts and around energized equipment and concentrated light with appropriate PPE
- Ability to work outdoors in Miami heat for extended periods during field testing
- Occasional travel to vendors, calibration labs, and field sites
Ready to Apply?
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