Software Engineer (Implementation)

Quanta•San Francisco, CA

9d•$180,000 - $225,000•Onsite

About The Position

Quanta is an AI-powered accounting and finance platform that fixes a major frustration for businesses: stale and slow financial data. We can do in seconds what takes our competitors weeks, which is why we’re trusted by many of today’s fastest growing startups. By rebuilding accounting from the ground up, we enable business decisions to be made with timely, complete, and explainable financial information. Many of today’s fastest-growing startups, including Paraform, Braintrust, Browserbase, and Mintlify, rely on Quanta as their financial foundation. The Team We are a tight-knit team of 17, working 4 days 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 opinionated about the future of finance and committed to building it together. 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.

Requirements

Hungry for ownership, we're looking for ambitious early-career engineers who want a level of ownership they wouldn't get for years at a large company.
At least 2 years of software engineering experience
Strong technical fundamentals across modern backend and frontend systems
Strong project management skills, you're going to own customer-facing projects end-to-end, and you'll need to be incredibly organized
Exceptionally fast learner, you will need to quickly understand accounting concepts, including their invariants
Strong communication & collaboration skills, you're going to be working closely with customers and accountants every day
You are excited about working in person with a collaborative team in San Francisco.

Nice To Haves

You are looking for linear career growth, with predictable ladders, levels, and promotion cycles.
You prefer clearly defined problems with detailed specs, rather than shaping solutions in ambiguous spaces.
You are uncomfortable working in a complex, judgment-heavy domain where correctness depends on context, not just code.
You prefer long, uninterrupted stretches of focused work, rather than balancing deep platform work with fast-moving customer needs.
You want to work in 1-2 week sprint cycles, rather than communicating progress to customers and stakeholders daily.

Responsibilities

Own customer implementations end-to-end
Take responsibility for understanding the problems our largest customers are facing before they onboard onto Quanta (i.e. the implementation phase).
Surface these problems by collaborating closely with our customers and our accountants.
Own the implementation end-to-end, working closely with customers, our accountants, and engineers to discover unknowns, scope platform gaps, and project manage the implementation.
Own the execution, where you will build customer-facing reconciliations, extend our core platform, and iterate quickly on internal tooling to scale our accountants.
Lean into AI as a force multiplier with correctness at the forefront
Work alongside engineers and accountants to explore how new tools, workflows, and agentic systems can change how we design, implement, and maintain our product and services.
Be responsible for building AI systems that are verifiable and correct.
Dive deep into accounting and understand its invariants, so you can build the right tools for AI to verify itself and design workflows that scale.
Model how businesses actually work
Work closely with accountants and the engineers leading our operational data model to apply, stress-test, and evolve these abstractions in real use.
Iterate on core primitives, object-level data models, and domain interfaces as you apply them to real business structures.