Software Engineer (Implementation)
Quanta
| Company | Quanta |
| Category | Engineering |
| Location | San Francisco |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Not stated |
| Salary | USD 180k–225k |
| Posted | 27 Jul 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (ashby) |
Description
QUANTA
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.
WHAT YOU’LL DO
Own customer implementations end-to-end
You will take responsibility for understanding the problems our largest customers are facing before they onboard onto Quanta (i.e. the implementation phase). You'll surface these problems by collaborating closely with our customers and our accountants.
You will 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.
You will 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
AI is moving quickly, and we see it as a chance to rethink how software gets built as a team.
You will 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.
You will be responsible for building AI systems that are verifiable and correct. You will d
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