Software Engineer (Staff)

Maximor AI•New York City, NY

8d•Onsite

About The Position

Maximor is an AI agent platform for finance. Our agents connect to ERPs, CRMs, billing, payroll, and banks — and automate the manual accounting work that consumes finance teams every month: reconciliation, journal entries, contract parsing, revenue recognition, and close. Finance teams review only the exceptions — every output is traceable and audit-ready. We've raised $9M led by Foundation Capital , with BoldCap, Gaia Ventures, Aravind Srinivas (CEO, Perplexity), and finance leaders from Zuora, Zoom, Ramp, Gusto, MongoDB, and the Big 4 — one of the largest seed rounds in the accounting category. The Day-to-Day Where Senior engineers own a module, Staff engineers own the platform layer every pod builds on. Your work multiplies the team — the abstractions you build let every pod ship faster, and the patterns you set become how the company does engineering. When a pod hits a problem no one else can crack, you're the one who makes it tractable. Staff at Maximor is depth of impact, not span of control — we don't stop writing code. Problems Worth Your Brain What's the right shape of a sub-ledger primitive that every agent in the company writes through — flexible enough to model any accounting workflow, rigid enough to keep an audit trail? How do you build an agent platform where pods ship reliable Audit-Ready Agents in days, not months — without each pod re-deriving the same eval, guardrail, and observability work? How do you encode auditability as a property of the system itself, not as something each pod has to remember to add? How do you build a close orchestration layer that's flexible enough for 1,000 different close calendars but rigid enough that an auditor can trust it? What does "engineering excellence" mean for non-deterministic systems in regulated environments — and how do you make it teachable to the next engineer who joins? How do you make sure the architectural decisions made in 2026 don't trap the company in 2029? We don't have these figured out. That's most of the appeal. A Few Strong Opinions The engineer who can't operate AI agents fluently is becoming obsolete, fast. Fluency with Claude, Cursor, and internal agent tooling is a second cortex. "Backend vs. frontend" is dissolving. The agents do the typing. The constraint is product judgment, system design, and the ability to close the loop from problem to shipped feature. Staff engineers ship full-stack when the work calls for it. The pod is the unit of leverage. Two engineers who can hold an entire module in their heads ship more than ten engineers who each own a slice. Specialization across pods, generalist within them. Staff engineers raise the ceiling for every pod. The accountant + engineer loop is the moat. Engineers who sit with controllers and build from what they see compound faster than the ones who don't. What Great Looks Like Here You can learn an accounting workflow in an hour and have it in code by the end of the day. A controller walks you through a prepaid amortization across 80 entities; you spot the edge cases she didn't think to mention. The single most important skill on the team. You're a current or future founder. You scope your own work, think about the customer, own your decisions. You solve problems end to end. The team is split vertically, so every engineer owns a part of the product and makes decisions across the LLM pipeline, infrastructure, backend, and UX. You care about getting it right. A 100% solution beats an 80% one. When something breaks, you go to root cause. You don't graduate out of code. You write the trickiest reconciliation logic yourself.

Requirements

8+ years of software engineering with deep specialization in distributed systems, ledger / transactional systems, data infrastructure, integration platforms, or AI/agent platforms.
Strong backend chops in a modern language — Python, Go, Java, Rust, or similar. (Our stack is Python; if your deep experience is elsewhere, ramp fast.)
Ships TypeScript when needed.
Built load-bearing systems multiple teams depended on, and made architectural calls that compounded for years.
Worked at an early-stage startup (pre-seed through Series B).

Nice To Haves

Prior Staff or Principal IC experience at a high-growth startup.
Worked at an accounting, fintech, or ERP-adjacent SaaS startup, or built ledger / sub-ledger systems.
Designed and operated AI agent platforms in production — evals, guardrails, observability, orchestration.
Operated systems under audit or regulatory scrutiny — SOX, SOC 1/2, financial audit.
Understand why "right" matters more than "fast" on certain code paths.

Responsibilities

Own the platform layer every pod builds on.
Build abstractions that let every pod ship faster.
Set patterns that become how the company does engineering.
Solve problems that no one else can crack.
Ship full-stack when the work calls for it.
Raise the ceiling for every pod.
Learn an accounting workflow in an hour and have it in code by the end of the day.
Scope your own work, think about the customer, and own your decisions.
Solve problems end to end.
Make decisions across the LLM pipeline, infrastructure, backend, and UX.
Go to root cause when something breaks.
Write the trickiest reconciliation logic yourself.