What are the responsibilities and job description for the Founding AI/ML Engineer position at Prismera?
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. We handle everything from document understanding and data extraction to agentic portfolio workflows and deal execution.
We are backed by industry-leading executives, trusted by publicly traded REITs and national operators, and scaling into the largest institutional CRE firms in the world.
The Role
This is a founding AI/ML engineering role. You will own Prismera's AI systems end-to-end: ingestion pipelines, LLM orchestration, retrieval infrastructure, and the production systems that enterprise customers rely on daily.
You are building the technical foundation, the systems, and the engineering culture from the ground up. Architecture decisions, tooling choices, and product direction on the AI side are yours to drive. You will ship to production and see your work in the hands of customers managing billions in real assets within your first weeks.
This is the stage where one engineer's work defines the trajectory of the company.
What You'll Do
- Build and own document understanding systems: extraction, classification, and structured output from complex, messy, real-world documents across hundreds of formats with zero standardization.
- Design and ship agentic workflows that automate multi-step processes end-to-end, chaining reasoning across documents, deadlines, and decision points.
- Own retrieval infrastructure: how we represent, index, and surface the right information across millions of pages of private enterprise data.
- Evaluate and integrate new models, architectures, and tooling as the AI landscape evolves. You decide what Prismera runs on.
- Work across the full AI/ML surface area.
Who You Are
- 1–3 years of experience building and shipping AI/ML systems in production. What matters is what you've built, not how long you've been building.
- Strong software engineer first. You write production code, not notebooks.
- Hands-on experience with LLMs in production where mistakes can cost millions.
- Comfortable with document processing, information extraction, or NLP pipelines
- Experience with cloud infrastructure and the ability to own your own deployments.
- You move fast, default to shipping, and iterate based on what you learn from real users.
- Autonomous and high-ownership. You don't wait to be told what to build next.
- Bonus: experience in financial services, real estate, or other domain-heavy enterprise environments.
Why Now
We have enterprise customers, real revenue, and a product in a market where the incumbent software is decades old and was never designed for what AI makes possible. You would be joining at the earliest stage with the most leverage: not to maintain what exists, but to build what comes next.