Data Center Architect
Davis AI
Data Center Architect
Davis AI
AI-driven real estate development and design
TLDR; Davis is looking for an architect who has already run data center feasibility studies on their own, and who can answer the question a client asks in front of a site: how many megawatts can this land absorb. We expect three to five years on the data center product, with two or three projects seen end to end.
Davis is an AI-native real estate company accelerating early-stage development and architectural design. Today developers coordinate 4-5 fragmented stakeholders over weeks or months. Soon they'll need only one: Davis.
We turn every input that shapes a development decision into decision-ready outputs: investor-grade feasibility studies, investment analysis, and architect-certified designs, delivered in days. Every stage pairs our proprietary AI systems with expert review, so velocity never comes at the cost of reliability.
We closed a $5.5M pre-seed co-led by Heartcore Capital and Balderton Capital, with Yellow, Evantic and Entrepreneur First, alongside angels from the founding teams of Spacemaker, Black Forest Labs, Hugging Face, Supabase, Cleo and Spore Bio. We already work with leading developers and expect to support hundreds of projects over the coming year, deepening our research, our hiring, and our coverage of the development process end to end.
The data center market is structuring fast, operators and landowners are hunting for sites, and the question they ask is one of capacity: how many megawatts of IT load does this land carry, under what scheme, and on what conditions. We answer in days where the market takes weeks. You will be the person who answers for that number.
You will run a portfolio of test fits and data center feasibility studies, with occasional work on large logistics and industry. Under the supervision of a lead architect, you take these projects from first capacity through to schematic design, and you present them to the client.
Establish a site's capacity in IT megawatts, working from the local zoning rules and operating constraints, and set out the assumptions behind it.
Qualify the applicable land-use category and the environmental-classification regime for industrial facilities, and derive from them the permitted height, the setbacks and the siting conditions.
Draw the data halls at their real grid, fully laid out, with their aisles, their air-handling units and their structural grid.
Compose the industrial site plan: service yards, a perimeter heavy-vehicle road, loading docks, retention basins, planted buffers, access and parking.
Arbitrate between schemes, one level, two levels or more, while respecting the slab-to-slab height and the zoning height cap.
Name the questions to put to the operator: cooling system, density per rack, electrical redundancy, hall dimensions, height.
Carry your number in front of the client, and defend it under challenge.
Place the project on its critical path: grid connection, environmental permitting, ecological surveys, preventive archaeology.
Formalize data center best practice, translating the sizing cascade, the grids and the thresholds into criteria our AI teams can use.
Qualify the model's outputs, saying what is right, what is wrong, and on what grounds.
Work across the product, tech and real estate teams, inside the tool's continuous-improvement cycles.
Take part in project reviews and exchange with the other architects to improve the methods and the quality of the deliverables.
Contribute to the team's graphic standards.
Education: a degree in architecture.
Experience: we count projects as much as years. Three to five years on the data center product, with two or three projects seen across their full cycle. One of them should be a project you carried yourself, from capacity through to permit or schematic design. A background in large logistics or industrial buildings is a valid base, provided you add that data center experience to it.
Software: mastery of Rhino and Revit is essential, and AutoCAD is expected.
Appetite for digital tools and AI: you do not need to code, but the drive to fold these tools into your practice and push it forward is essential.
Speed and synthesis: our clients decide fast, on a number. You need to produce a credible, well-drawn scenario in hours, cut to the essential on ambiguous cases, and know what level of detail serves the decision at each phase.
Product knowledge, the sizing cascade of a data center, hall, power, cooling, telecom and logistics, the slab-to-slab height and what it imposes, the rack-and-aisle grid, electrical redundancy, the order of magnitude of a PUE.
Applied regulatory fluency, the land-use sub-category and the 2023 ruling that reclassified data centers, the environmental-classification headings and the threshold that triggers a full environmental permit, height and setback rules, no-net-land-take targets and designation as a project of major national interest, rooftop renewable-energy requirements.
Buildable capacity, linking a rule to its quantified effect on a volume, and a volume to an installable power.
Industrial site planning, heavy-vehicle access, turning circles, fire safety, water management, insertion and edges.
Graphic production, plans, sections and diagrams that make a capacity argument legible to an investor.
Ownership of the subject, presenting, arguing and defending a number in front of a client who contests it. We are looking for someone who has owned the subject end to end, assumptions, number and client presentation.
Rigor and a sense of synthesis, especially on ambiguous cases.
Structuring information, organizing what you produce so that others, human or machine, can use it.
An ability to work across the product, tech and real estate teams.
A command of technical English, the vocabulary of the sector being largely English-speaking.
Take part in a genuine transformation of the real estate profession, and co-build the next generation of feasibility standards alongside a high-caliber technical team.
You will set Davis's data center method, and it will serve every project that follows.
See your work in every deliverable, and correct the tool when it gets things wrong.
Join a young company, where the methods and the tools are still being built, and where your expertise shapes the way we work.
Fixed-term or permanent depending on the case, to discuss together
Offices in the center of Paris 2e
Private health insurance covered
Meal vouchers
Gym membership covered
50% of commuting costs reimbursed
Mehdi (CEO) grew up in a family of architects and has lived this problem firsthand. He's a repeat founder who bootstrapped his first startup at 20, and graduated from Sciences Po and HEC Paris. Amine (CTO) is an AI researcher from École Polytechnique who worked extensively on discrete diffusion and turned down a PhD with Google DeepMind to build Davis. They started working together in July 2025 at Entrepreneur First's first European residency, a two-month lock-in in a German castle.
Today we're a team of 12: technical profiles from Polytechnique, ENS and INRIA alongside architects and deep real estate expertise.
We're small with an extremely high bar. If you want to work deeply on hard problems and see your work reach clients within days, you're the one we need.
Real estate is a $13 trillion industry that technology has largely bypassed. The professional services that feed it (design, engineering, feasibility, permitting) represent hundreds of billions in spend that no one has seriously automated.
Proptech spent the last decade selling SaaS on the edges of these workflows. It didn't work, for two reasons: no professional wants another tool to learn, and no tool can automate work that runs on expert judgment. Davis makes a different bet. We don't sell tools, we sell the work: AI-generated, expert-validated, delivered in days instead of weeks. Every project compounds our data advantage across typologies, geographies and regulatory contexts.
If you're drawn to what we're building but don't meet every requirement, we still want to hear from you. Studies show that women in particular tend to apply only when they meet 100% of the criteria. If that's you, please don't let that hold you back. We'd love to receive your application.
Davis AI helps real estate developers speed up early-stage projects by delivering finished feasibility studies and architectural designs through an integrated service that combines proprietary AI with in-house architects. Its technology translates regulatory, technical, and market data into constraints for a generative model to create site analyses, ROI, regulatory diagnostics, volumetrics, floor plans, and space planning, with human review to ensure quality. The company differentiates itself by providing end-to-end outputs rather than software tools, relying on a tightly coordinated process that blends data-driven design with architectural practice. Its goal is to cut development timelines from months to days, enabling faster and more reliable real estate investment and project delivery.
Explore more opportunities at Davis AI