Staff Software Engineer, Accounting

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:

Transform our home-grown accounting system into a foundational primitive, defining the interfaces that other teams consume.
Define scalable accounting infrastructure, owning architectural decisions end to end and ensuring execution follow-through across the company.
Apply AI to address the long-tail of data integrity challenges; create reusable patterns for reconciling increasingly complex money movement.
Partner with engineering leadership to shape roadmaps, surface technical risk early, and ensure we are building the right things the right way.

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.
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.
Are comfortable in high-stakes, domain-rich systems. You may not know fund accounting today, but you’ve built systems where correctness is non-negotiable—financial, healthcare, infrastructure, or similar. You build deep domain expertise quickly by working closely with subject-matter experts.
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.