Staff Software Engineer, Funds

We’re solving some of the hardest problems in venture capital and private markets. You’ll work with a team that values precision, urgency, and long-term thinking. If you want to shape how startups are funded and built, this is the place.

We exist to accelerate innovation by increasing the number of successful startups in the world. We do this by building the financial infrastructure that makes it easier for more people to invest in world-changing companies.

AngelList is the nexus of venture capital and the startup community. We support $171B+ in assets and have powered investments into over 13,000 startups—over 300 of which are unicorns. Today, 57% of top-tier U.S. VC deals involve investors on AngelList. While our scale is large, our ambition is larger.

If you're excited to build the future of private markets, come build with us.

You will have the opportunity to:

Define the architecture of the new GP dashboard as we rebuild it from the ground up -  setting the foundational patterns the team reaches for as the experience scales to institutional funds.
Own the product-level decisions that determine what self-serve looks like for institutional GPs, working closely with PMs and customers to shape what gets built, not just how.
Identify where AI can eliminate operational friction in fund management workflows. Turn multi-step processes that currently require an operator into something a GP can do in seconds.
Drive technical direction across the boundaries between Funds and adjacent systems (LP onboarding, subscriptions, treasury) so that the GP experience is coherent end-to-end.
Raise the ceiling of a small, high-ownership team through design reviews, architectural patterns, and the kind of judgment that makes senior engineers around you better.

You most likely:

Have operated at staff level or equivalent. You are highly autonomous, have had impact beyond your immediate team, and have a track record of architectural decisions that held up as systems scaled.
Are as comfortable on a customer call as in a systems design review, able to understand what a GP actually needs and ship it without a lengthy handoff chain.
Have demonstrated a multiplier effect on engineering teams. You’ve been the person who defined the patterns a team reached for—and the team was measurably better for it.
Have a deep love of startups, having worked at one (or potentially started one). The domain is part of the job.
Have strong hands-on coding ability. You write production code regularly, review others’ work rigorously, and have no interest in becoming a purely advisory engineer.
Are curious about AI as applied infrastructure—not hype, but genuine interest in where it can make financial workflows more accurate, more automated, and more trustworthy.