USASoftware Engineer (Implementation)
1 мес. назад
180k–225k USD / yearUSAJuniorOnsite
Implementation-focused software engineer role at an AI-powered accounting and finance platform.
Условия
- Competitive early-stage salary ($180K-$225K)
- Competitive early-stage equity
- Health, dental, and vision insurance
- 401(k)
- Commuter benefits
- Wellness stipend
- Take-what-you-need paid vacation
- Paid lunches and dinners in the office
- All equipment and tools you need to be productive
Другое
- 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 as their financial foundation.
- 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.
- 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.
- You will take responsibility for understanding the problems our largest customers are facing before they onboard onto (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.
- 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 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.
- A core part of 's differentiation is how we model businesses in software.
- Accounting reflects how a company operates, but that reality is messy and full of exceptions, and few abstractions work across companies without careful design.
- You will work closely with accountants and the engineers leading our operational data model to apply, stress-test, and evolve these abstractions in real use. This includes iterating on core primitives, object-level data models, and domain interfaces as you apply them to real business structures.
- Getting this right has outsized impact. These models determine what can be automated, what questions the system can answer, and how confidently finance teams can rely on the system.
- 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 .
- 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.
- You have successfully owned the implementation of 3-5 customers
- You have deep familiarity with ’s core systems and are comfortable working where correctness is most critical.
- You have owned and shipped improvements used daily by internal teams and customers.
- You have shaped at least one core abstraction that increases flexibility without compromising trust.
- You have helped define how the team uses AI in practice to increase leverage.
- You feel strong ownership over outcomes, not just code.