Founding Engineer
prismeraNew York (NY)
About the role
About Prismera Prismera builds AI for commercial real estate portfolio operations. Our platform ingests unstructured portfolio documents and turns them into structured intelligence that powers how institutional owners and operators manage portfolios worth billions. Over a billion square feet of commercial real estate is actively run on Prismera today. We are backed by industry-leading executives, including operators who've built and run some of the largest commercial portfolios in the country, trusted by publicly traded REITs and national operators, and scaling into the largest institutional CRE firms in the world.
The Role:
You'll be one of a small number of engineers working directly with the founders, owning full surface area of a production system institutional customers already depend on. You'll take a raw idea from a client meeting or investor conversation, a new workflow, a new failure mode in how leases get parsed, a new way owners want to interact with their portfolio, and turn it into shipped, production-grade product without adding technical debt or bloating the interface. There's no platform team to hand things to. If it's broken, it's yours.
What You'll Do:
Build and own core product workflows across the stack: frontend systems, backend services, APIs, databases, and the interfaces customers interact with daily.
Design and ship interfaces that make complex portfolio operations, AI workflows, and enterprise data feel simple, fast, and intuitive.
Work directly with customers to understand workflows, identify friction points, and rapidly translate operational reality into production software.
Operate with high autonomy across product, engineering, and UX.Who You Are / Requirements 1-3 years shipping production full-stack software. TypeScript/React on the frontend, Python services on the backend.
Strong relational data modeling: you can design a schema for messy, hierarchical real-world data (documents, versions, amendments) and defend your tradeoffs.
Hands-on AWS in production: containerized services (ECS/Fargate or similar), IAM, networking basics, and you've debugged something at 2am because of it.
Experience building on LLM APIs beyond a chat wrapper: structured extraction, evals, handling nondeterminism, knowing when the model is wrong.
Comfortable owning a feature end-to-end with no spec, no designer, and no platform team
Why NowWe have enterprise customers, real revenue, and a product entering a market where the incumbent software was never built for what AI now makes possible. You'd be joining at the earliest stage with the most leverage, not maintaining someone else's system, but defining how this gets built from here.
Location: Flatiron, Manhattan. Five days a week, in person.
Before you apply
Applying takes about a minute. These four things decide how fast it moves after that.
Your profile is current
It's what we read first. Occupations, seniority and locations matter more than a long history.
Two examples you can talk through
Not a portfolio — just two pieces of work where you can explain the decisions and what you'd change.
A number in mind
What you're on now and what would make you move. We negotiate better when we know both.
Your notice period
Employers plan around it, and it's the question that stalls offers most often.
Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.
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