Maximor AI Senior Software Engineer

Maximor AI — Senior Software Engineer Type: Full-time | On-site | New York City, NY Compensation: $170,000–$220,000 + 0.1%–0.35% equity Hiring count: 1 Visa sponsorship: None available Reports to: Founding engineering team About Maximor 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. Founded: 2023 | Team size: 1–10 | Total funding: $9MIndustry: AI ToolsWebsite: maximor.aiOffice: New York City, NY 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. Why Candidates Should Join Full domain ownership: Each senior engineer owns a finance domain end-to-end — no PM writing specs, no architecture committee to approve decisions. Frontier backend problems: 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. Strong backing: $9M led by Foundation Capital, with the CEO of Perplexity and finance leaders from Ramp, Gusto, and Zuora behind the company. Intake Call Summary Not provided on the role page. The Role 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. What You'll Be Doing 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 Design and build AI agents that reason across fragmented financial data, with verification, guardrails, observability, and evaluation systems for non-deterministic outputs Ingest, normalize, and reconcile data from ERPs, banks, payroll platforms, billing systems, CRMs, and email into a unified financial context layer Ship idempotent, audit-ready write-backs to systems of record with full traceability Sit directly with controllers and finance teams to learn workflows, then translate that understanding into shipped software Operate AI coding agents fluently as a daily part of the engineering workflow, owning decisions across the LLM pipeline, infrastructure, backend, and product surface Tech stack: Python (backend engineering also in modern languages such as Go, Java, or Rust) Requirements 5+ years backend or infrastructure engineering Seed-to-Series B startup OR high-growth company (Rubrik, Databricks, Ramp, Brex) OR top large-tech (Meta, Google, Stripe, LinkedIn) Hard backend systems: distributed pipelines, ledger/transactional systems, integration platforms, or workflow engines Resume showing architecture detail and clear personal ownership NYC in-person Fintech, ERP, or accounting-software background a strong plus Startup hours, 6 days a week, 9am to 7pm or 8pm Green Flags Startup or high-growth pedigree with real ownership Hard backend systems builder Domain depth in finance, fintech, or enterprise integrations Production AI agent experience Red Flags Frontend-heavy background with shallow backend depth Resume lists technologies without depth or ownership evidence Multiple short stints (more than one role under one year) Role Details Salary — $170,000–$220,000 Equity — 0.1%–0.35% On-site policy — In-person at the NYC office; startup hours, 6 days a week, 9am to 7pm or 8pm Visa sponsorship — None available Employment type — Full-time Location — New York City, NY Screening Questions Not provided on the role page. Interview Process Stage 1 — Pending Approval — Candidates awaiting initial approval. Stage 2 — Founding engineer screen — Initial technical and cultural-fit conversation with a founding engineer. Stage 3 — Take-home assignment (5–8 hours) — Demonstrates backend engineering depth and ownership approach. Stage 4 — Debrief on take-home — Walkthrough and discussion of take-home work. Stage 5 — On-site (5–6 hours) — Deep technical and team interviews with engineers and founders. Stage 6 — Offer Extended Stage 7 — Candidate Hired — Candidate accepts and starts. Ideal Companies & Backgrounds 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 #J-18808-Ljbffr David Joseph