Engineering Manager

Quanta•San Francisco, CA

1d•$225,000 - $325,000•Onsite

About The Position

Quanta is an AI-powered finance platform built for fast-growing companies. Every company relies on accounting as its source of truth, but the tools today are manual, fragmented, and not designed for how modern businesses operate. We're building the system of record for finance - one that owns the data layer and uses AI to automate and abstract away the operational burden. The result is a real-time, intelligent financial backbone that goes far beyond traditional accounting software. Many of today's fastest-growing startups - Decagon, Braintrust, Browserbase, Mintlify - rely on Quanta as their financial foundation. The Team We are a tight-knit team of 17, working fully in-person in downtown San Francisco. Our backgrounds sit at the intersection of finance and engineering. As a group, we have built accounting systems at Affirm, ledgers at Stripe and Robinhood, and companies from the ground up. We have passed CPA exams, built finance teams from one to dozens, shipped 0→1 products, and scaled systems that support billions in transactions. We understand our customers because we have been in their shoes. We care deeply about correctness, trust, and building systems that last. We are defining the Operational Ledger, a new financial foundation for how businesses truly understand themselves. If you want to work on deep, consequential systems, financial data is one of the hardest places to do it well. Accounting sits at the center of every business, yet today it is slow, opaque, and stripped of the context needed to answer real questions. We use accounting as the raw material, not the end goal. By operating directly on real customer data and real workflows, we turn messy, judgment-heavy financial data into a reliable, queryable system of record. What We’re Building We are building the Operational Ledger by staying unusually close to the real work. Today, that means we do the accounting ourselves for a focused set of customers. This is not a go-to-market shortcut. It is how we learn where existing systems fail, where judgment is required, and where automation actually creates leverage. Because we operate directly on real financial data and real workflows, our iteration loop is tight. We solve concrete automation problems that exist today, not hypothetical problems framed around what AI might do someday. The product evolves directly from what breaks, what repeats, and what slows teams down in practice. This approach lets us build systems that are correct, explainable, and ready to support much more powerful interaction layers over time. The goal is not just faster accounting. It is to establish a financial source of truth that can support querying, modeling, and plain-language exploration with confidence. This is how we earn the right to define a new category of financial systems. The Role We're fresh off a Series A led by Accel, with real budget to grow the engineering team - and we're an engineering leader to do so. You'll be the sole engineering manager, leading a high-caliber team of 7 with backgrounds from Stripe, Affirm, Robinhood, Cash App, Meta, Airbyte, and more. You'll also sit on the company leadership team, working closely with the CEO (who comes from an engineering background), and helping shape company strategy and how we operate - not just how engineering runs. A big part of this role is inventing what engineering effectiveness looks like in the AI era. We're a small, greenfield team with no inherited process and no organizational debt. The tools, workflows, and culture of how we build are still being defined. The people joining now are the ones who shape that. We are also open to making this a Head of Engineering role for the right candidate.

Requirements

Experience managing and scaling engineering teams at a startup, ideally as the first or sole engineering manager
Track record of hiring strong engineers and closing candidates who had other options
Technical depth that earns respect - you can mentor on architecture, review hard problems, and engage seriously with a complex domain
Comfort operating in high-ambiguity environments where the playbook doesn't exist yet
Opinionated about engineering culture and effectiveness, and willing to push on it
You're excited about working in person in San Francisco.