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Founding Engineer (Full Stack)

About the Role This is a founding engineering role at an early-stage construction technology startup using AI and computer vision to automate blueprint analysis, material takeoffs, and cost estimation. You will be one of the first...

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Clera (ashby) San Francisco, California, United States Source published Sep 19, 2026 Verified 1 hour ago
✓ 80% verification score · Source: Clera (ashby) · Always confirm final requirements on the original source.
Complete source information imported The available role or programme description, requirements, benefits and source facts were imported from the public official endpoint and formatted for reading.
EmploymentFull Time
CountryUnited States
DepartmentEngineering

Overview

About the Role This is a founding engineering role at an early-stage construction technology startup using AI and computer vision to automate blueprint analysis, material takeoffs, and cost estimation. You will be one of the first engineers on the team, shaping both the product and the engineering culture from the ground up. The work directly supports making housing and infrastructure more affordable and accessible. What You'll Do Build intuitive, polished UIs that surface computer vision model outputs for end users. Tackle complex geometric problems, streaming systems, and sophisticated user interactions. Rapidly prototype new features and iterate on them based on direct user feedback. What We're Looking For Strong React and TypeScript skills combined with full-stack engineering ability. Python proficiency and comfort solving open-ended, math-oriented problems. Demonstrated track record

Full job description

Full Job Description

About the Role

This is a founding engineering role at an early-stage construction technology startup using AI and computer vision to automate blueprint analysis, material takeoffs, and cost estimation. You will be one of the first engineers on the team, shaping both the product and the engineering culture from the ground up. The work directly supports making housing and infrastructure more affordable and accessible.

What You'll Do

  • Build intuitive, polished UIs that surface computer vision model outputs for end users.

  • Tackle complex geometric problems, streaming systems, and sophisticated user interactions.

  • Rapidly prototype new features and iterate on them based on direct user feedback.

What We're Looking For

  • Strong React and TypeScript skills combined with full-stack engineering ability.

  • Python proficiency and comfort solving open-ended, math-oriented problems.

  • Demonstrated track record of taking a product from 0 to 1, ideally with real traction or paying customers.

  • Solid computer science fundamentals or an exceptional project portfolio that demonstrates equivalent ability.

  • Experience as a founder, founding engineer, or early employee at a startup.

  • Familiarity with Tailwind CSS is a plus.

  • Background in construction, real estate, or PDF workflows is a bonus.

  • Empathetic, honest communicator who is product- and customer-oriented rather than primarily research-focused.

  • Genuinely motivated by the mission of making housing more affordable.

  • Exceptional recent graduates with strong fundamentals and hustle are welcome to apply.

  • US citizenship required; visa sponsorship is not available.

Compensation & Benefits

Base salary: $100,000 to $180,000 USD annually. Equity is expected given the founding-team nature of the role. Visa sponsorship is not available.

Location

On-site in San Francisco, California, United States, five days per week.

Tips for this job

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  1. Tailor the CV and application to the responsibilities and required skills stated on the official employer page.
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  3. Confirm location, work authorization, remote restrictions and sponsorship terms before applying.
  4. Apply through the original employer or official recruitment destination shown on this page.

Verification notes

Discovered directly from the employer’s public Ashby Job Postings API. The complete public role content and compensation metadata were normalized into safe candidate-facing sections.

Original authoritative source

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