Maximor AI — Senior Software Engineer

<div><h3>Maximor AI — Senior Software Engineer</h3><p><b>Type:</b> Full-time | On-site | New York City, NY<b>Compensation:</b> $170,000–$220,000 + 0.1%–0.35% equity<b>Hiring count:</b> 1<b>Visa sponsorship:</b> None available<b>Reports to:</b> Founding engineering team</p><h3>About Maximor</h3><p>Maximor is building the AI operating system for the CFO office, connecting directly to a company's existing finance stack to automate the full order-to-cash cycle, record-to-report process, treasury management, and financial reporting. Its Unified Finance Context layer captures transactions, policies, contracts, and accounting judgment, powering Audit-Ready AI Agents that can reason, explain their decisions, and elevate uncertainty.</p><p>Founded: 2023 | Team size: 1–10 | Total funding: $9MIndustry: AI ToolsWebsite: maximor.aiOffice: New York City, NY</p><p>Backing (from outreach template + role body): $9M led by Foundation Capital, alongside Aravind Srinivas (CEO of Perplexity) and finance leaders from Ramp, Gusto, and Zuora.</p><h3>Why Candidates Should Join</h3><ul><li><b>Full domain ownership:</b> Each senior engineer owns a finance domain end-to-end — no PM writing specs, no architecture committee to approve decisions.</li><li><b>Frontier backend problems:</b> Building AI agents finance teams and auditors can trust, turning messy enterprise integrations into a unified source of truth, and orchestrating durable, replay-safe workflows across flaky stateful systems.</li><li><b>Strong backing:</b> $9M led by Foundation Capital, with the CEO of Perplexity and finance leaders from Ramp, Gusto, and Zuora behind the company.</li></ul><h3>Intake Call Summary</h3><ul><li>Not provided on the role page.</li></ul><h3>The Role</h3><p>A high-ownership engineering seat where each senior engineer takes full responsibility for a finance domain — from the LLM pipeline and infrastructure through to the customer-facing surface — working directly with controllers, accountants, and CFOs to understand the problem before building the system.</p><h3>What You'll Be Doing</h3><ul><li>Own a finance domain end-to-end (revenue, cash, close, reporting, payroll, fixed assets, tax, or controls) and ship it with a pod of two to three engineers</li><li>Design and build AI agents that reason across fragmented financial data, with verification, guardrails, observability, and evaluation systems for non-deterministic outputs</li><li>Ingest, normalize, and reconcile data from ERPs, banks, payroll platforms, billing systems, CRMs, and email into a unified financial context layer</li><li>Ship idempotent, audit-ready write-backs to systems of record with full traceability</li><li>Sit directly with controllers and finance teams to learn workflows, then translate that understanding into shipped software</li><li>Operate AI coding agents fluently as a daily part of the engineering workflow, owning decisions across the LLM pipeline, infrastructure, backend, and product surface</li></ul><p><b>Tech stack:</b> Python (backend engineering also in modern languages such as Go, Java, or Rust)</p><h3>Requirements</h3><ul><li>5+ years backend or infrastructure engineering</li><li>Seed-to-Series B startup OR high-growth company (Rubrik, Databricks, Ramp, Brex) OR top large-tech (Meta, Google, Stripe, LinkedIn)</li><li>Hard backend systems: distributed pipelines, ledger/transactional systems, integration platforms, or workflow engines</li><li>Resume showing architecture detail and clear personal ownership</li><li>NYC in-person</li><li>Fintech, ERP, or accounting-software background a strong plus</li><li>Startup hours, 6 days a week, 9am to 7pm or 8pm</li></ul><h3>Green Flags</h3><ul><li>Startup or high-growth pedigree with real ownership</li><li>Hard backend systems builder</li><li>Domain depth in finance, fintech, or enterprise integrations</li><li>Production AI agent experience</li></ul><h3>Red Flags</h3><ul><li>Frontend-heavy background with shallow backend depth</li><li>Resume lists technologies without depth or ownership evidence</li><li>Multiple short stints (more than one role under one year)</li></ul><h3>Role Details</h3><ul><li><b>Salary</b> — $170,000–$220,000</li><li><b>Equity</b> — 0.1%–0.35%</li><li><b>On-site policy</b> — In-person at the NYC office; startup hours, 6 days a week, 9am to 7pm or 8pm</li><li><b>Visa sponsorship</b> — None available</li><li><b>Employment type</b> — Full-time</li><li><b>Location</b> — New York City, NY</li></ul><h3>Screening Questions</h3><ul><li>Not provided on the role page.</li></ul><h3>Interview Process</h3><p><b>Stage 1 — Pending Approval</b> — Candidates awaiting initial approval.<b>Stage 2 — Founding engineer screen</b> — Initial technical and cultural-fit conversation with a founding engineer.<b>Stage 3 — Take-home assignment (5–8 hours)</b> — Demonstrates backend engineering depth and ownership approach.<b>Stage 4 — Debrief on take-home</b> — Walkthrough and discussion of take-home work.<b>Stage 5 — On-site (5–6 hours)</b> — Deep technical and team interviews with engineers and founders.<b>Stage 6 — Offer Extended</b><b>Stage 7 — Candidate Hired</b> — Candidate accepts and starts.</p><h3>Ideal Companies &amp; Backgrounds</h3><p>Not provided as a distinct section on the role page. The Requirements name the following as example pedigree companies: High-growth — Rubrik, Databricks, Ramp, Brex Top large-tech — Meta, Google, Stripe, LinkedIn</p></div><br />#J-18808-Ljbffr