| Location | San Francisco, California |
| Website | https://lumai.ai/ |
We are looking for a technically deep and commercially astute Solutions Architect to own the technical heart of our customer engagements as we bring the world's first optical compute inference platform to market. You will be the person who turns a customer's interest into a credible technical opportunity.
You will lead deep technical discovery with the most demanding customers in the industry – hyperscalers, neoclouds, frontier AI labs, and national laboratories – and translate what they need into a Lumai-based solution. You will work hands-on with our benchmark team to model and prove performance against real customer workloads, and you will author the technical proposals and responses that allow a customer to make the argument for Lumai inside their own organisation.
This is an early-stage role where you will help write the playbook. You will be as comfortable in a benchmarking discussion with a customer's ML and performance engineers as you are presenting a solution to their technical leadership, and you will act as a vital channel back into our own product and engineering teams, ensuring the voice of the customer shapes what we build next. In the near term, much of the work will be focused on pre-hardware performance modelling and simulation.
Partner with Lumai’s VP Business Development, owning the technical relationship with each customer
Conduct deep technical discovery with customer ML, inference and infrastructure engineering teams – their models, serving stacks and performance targets
Translate customer requirements into a Lumai-based solution, mapping needs against both near-term and roadmap solutions
With business development, define the shape of an engagement – benchmark, proof of concept, reference architecture, or statement of work
Work hands-on with Lumai's benchmark team to scope, run, and interpret benchmarks against GPU and other baselines, and own the presentation of results
Be the voice of the customer in refining Lumai’s customer-facing simulation framework, and support customers in running their own workloads on it
Build performance and TCO models – throughput, latency, cost and energy per token – showing how Lumai compares with incumbent solutions on customer workloads
Produce the technical case for Lumai – proposals, solution documentation, and responses to RFIs, RFPs, and tenders
Design and deliver demos and technical workshops for customer technical teams
Work with engineering to define how Lumai integrates with customer software stacks – serving frameworks, runtimes and orchestration
Feed customer requirements, evaluation feedback, and roadmap reactions back into product and engineering, informing the Lumai roadmap
At least five years’ experience in a solutions architecture, technical pre-sales, or senior field engineering role within AI infrastructure, high-performance compute, semiconductors, or a comparable deep-tech hardware domain
Strong working knowledge of LLM inference at scale – model architectures, serving frameworks such as vLLM, TensorRT-LLM or SGLang, batching and parallelism, and the trade-offs between throughput, latency and cost
Hands-on experience benchmarking and analysing the performance of AI workloads, including performance modelling, with the credibility to defend results to customer ML and infrastructure engineers
Demonstrated ability to lead technical discovery with sophisticated customers and translate requirements into a solution
Comfortable operating in a fast-moving, sometimes ambiguous, pre-product environment
Direct experience selling into, or working within, hyperscalers, neoclouds, frontier AI labs, or national laboratories
Awareness of the AI accelerator competitive landscape
Background or genuine curiosity in novel compute – photonics, optical computing, or other post-silicon architectures
Experience with accelerator software stacks – compilers, kernels and runtimes – or bringing a new accelerator into an existing ML ecosystem
Familiarity with data centre constraints – power, cooling, rack density and networking – sufficient to frame performance-per-watt and TCO arguments
San Francisco, Bay Area.
Lumai is the optical compute company building the next generation of AI infrastructure. Spun out of optics research at the University of Oxford in 2021, we compute with light instead of electrons. Our 3D optical technology carries out the matrix multiplications at the heart of AI inside beams of light travelling through free space, which lets it go beyond the limits of both silicon GPUs and integrated photonics.
In April 2026 we launched the world's first optical computing system to run billion-parameter large language models in real time. Our first optical computing server is now available for evaluation by hyperscalers, neoclouds, enterprises and research institutions.
Our work won the Falling Walls Award for Science Breakthrough of the Year 2025 and 'Best Overall Technology' at the OCP Future Technologies Symposium. We are headquartered in Oxford.
You'll work on a new kind of computer. Optical computing for AI has been promised for decades. We have a working system running real models, and the hard part left is taking it to volume.
Your work ships. We are moving from first product to volume production, so what you build this year goes into the servers our customers run.
You'll work across disciplines. Optical engineers, machine learning researchers, and hardware and software engineers solve problems together. You will learn things that don't appear on your job description.
The work matters beyond Lumai. AI's appetite for energy is one of the defining constraints of the next decade. Our mission is sustainable intelligence at global scale: AI that is faster, cheaper to run and far less power-hungry.
You'll join early. You'll have a real say in how we build the product, the team and the way we work.
Lumai is an equal opportunity employer. We make hiring decisions based on skills, experience and potential, and we welcome applications from people of all backgrounds. If you need an adjustment at any stage of the hiring process, let us know and we will do our best to support you.