Example Company
Software engineer
- Location
- San Francisco
- Type
- Full time
- Compensation
- $150k-$200k
- Posted
- 2 days ago
Join a team building useful software. Work closely with engineering and design to turn new ideas into products.
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Full Stack Engineer
- Type
- Full time
- Posted
- 8MO AGO
About the role
Location: San Mateo, CA (In-Person, Bay Area)
About Primepoint
Primepoint is building construction intelligence for the physical world. We transform massive, static construction datasets (drawings, specifications, revisions, submittals) into an interactive, AI-powered system that surfaces conflicts, answers complex questions, and reduces schedule and cost risk on $100M–$3B+ building projects.
We go beyond LLM wrappers. Our mission requires deep multimodal reasoning, document understanding, and applied computer vision at production scale.
Our founders built Facebook’s first computer vision team and helped launch Facebook AI Research, and also founded startups in neural video compression (acquired by Apple).
We are a technical team backed with $10M in seed funding and already working with paying customers spanning major hospital and large-scale commercial projects.
We are in-person in San Mateo because we believe tight collaboration accelerates product velocity.
The Role
We’re hiring a Full Stack Engineer who can build end-to-end product features in a highly ambiguous, high-ownership startup environment.
You will:
Own features from concept to deployment
Build complex, high-performance front-end systems (React)
Develop backend services (Python + Postgres)
Work on document intelligence, search, change detection, and large-scale data processing
Ship fast and iterate directly with customers
Collaborate closely with founders on product direction
This is not a “small-slice” big tech role. You will build real systems that customers use on billion-dollar construction projects.
What We’re Looking For
Must-Have
Strong full stack engineering ability (Python + Postgres + React)
Proven builder: shipped meaningful systems end-to-end
Comfortable operating with ambiguity and minimal hand-holding
Evidence of high performance (selective company, fast promotions, or exceptional output)
Embraces modern AI tooling (LLMs, code assistants, etc.)
Based in the Bay Area and willing to work in-person
Ideal, but not required
Experience with PDF processing, document parsing, or complex data pipelines
Distributed systems or search/indexing experience
Product-engineer mindset
Startup experience (founding or early-stage preferred)
Exposure to applied machine learning
Interview Process
Quick Recruiter chat
30-min Hiring manager conversation
Technical interview
Onsite collaborative problem solving session (LLM use encouraged)
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