Our platform gives institutional investors access to exclusive interviews with senior executives from the world’s best companies, plus a growing suite of AI-powered research tools. Clients include multi-billion-dollar funds across the US and Europe. You’d be joining a small, high-ownership group where every person shapes the product directly.
The Role
We’re hiring a senior full-stack engineer to build AI products that change how investors analyze companies. That means things like:
– An agent that reads 10-K filings across 30 countries and extracts supplier relationships, segment economics, and risk factors — automatically
– Interactive interfaces where an investor can interrogate a company’s entire filing history in conversation
– Document processing pipelines that turn thousands of pages of regulatory filings into structured, searchable data
You’ll own the full lifecycle: talking to customers, designing the solution, building it, deploying it, and iterating based on what you learn.
What We’re Looking For
Must have
– Full-stack TypeScript fluency — React, Next.js, PostgreSQL. You’re comfortable across the entire stack and can ship a complete feature alone.
– Product instinct — You’ve taken ideas from customer conversation to production. You make good decisions about what to build, not just how.
– Design sensibility — You build interfaces that are clean and intuitive. Comfort with Tailwind/CSS; you don’t need a designer to make something look good.
– AI-native workflow — You use AI tools (Claude Code, Cursor, Copilot, or similar) to move faster. You’re curious about LLMs and have opinions about how to build with them.
– Strong English communication — Our team is global and remote; our customers are primarily US-based.
– Experience building from zero — You’ve shipped products (at a startup, as a side project, or within a larger company) where you had to figure out the what, not just the how.
Bonus points
– Experience building products for investors or financial markets
– Hands-on work with LLM agents, context engineering, or RAG pipelines
– You’ve lived or worked abroad and thrive in distributed, cross-cultural teams
Why Join
– Interesting problems — Applying LLMs to messy, real-world financial documents is genuinely hard and unsolved. You won’t be wrapping ChatGPT in a UI.
– Direct impact — Small team, sophisticated customers, short feedback loops. Your work ships and matters.
– Ownership culture — Flat hierarchy. Everyone talks to customers. Information flows freely.
– Learning environment — The team is full of investors. You’ll develop real domain expertise in public markets, not just build software about it.
What We Offer
– Competitive market salary
– Option to earn equity
– Full setup — devices, tools, AI subscriptions, books, courses, conferences
– Madrid co-working space for those based locally
Hiring Process
1. Intro call — your background, what you’re looking for
2. Take-home project — a small, real problem from our domain (respectful of your time)
3. Technical deep dive — review your project together, discuss architecture and tradeoffs
4. Team & founder interviews — culture fit, vision, questions both ways
Apply
Send an email to careers@inpractise.com with:
– Your LinkedIn and GitHub profiles
– A brief note on why this role interests you
We’re always looking for exceptional engineers. If the timing isn’t perfect, reach out anyway.
…