Maximor AI — Senior Software Engineer

davidjoseph-co; New York (NY); On-site; USD 170,000 - 220,000; Full time

Job summary

Maximor AI in New York City is seeking a Senior Software Engineer to own a finance domain end-to-end, from the LLM pipeline to the customer-facing surface. You will collaborate with controllers, accountants, and CFOs to understand processes and then build durable software that automates the order-to-cash and reporting workflows.

You will design AI agents that reason over fragmented financial data, ensure guardrails and observability, and ship with full traceability across systems.

Qualifications

• 5+ years backend or infrastructure engineering experience.
• NYC in-person requirement.
• Fintech, ERP, or accounting-software background is a strong plus.
• Startup hours: 6 days a week, 9am–7pm or 8pm.

Responsibilities

• Own a finance domain end-to-end within a pod of 2–3 engineers.
• Design and build AI agents that reason across financial data with guardrails and observability.
• Ingest and reconcile data from ERPs, banks, payroll, billing and CRM into a unified context layer.
• Ship audit-ready write-backs to systems of record with full traceability.
• Work directly with controllers and finance teams to translate workflows into software.

Skills

Backend engineering

Infrastructure engineering

Distributed systems

Tools

Python

Go

Java

Rust

Job description

Maximor AI — Senior Software Engineer

Type: Full-time | On-site | New York City, NYCompensation: $170,000–$220,000 + 0.1%–0.35% equityHiring count: 1Visa sponsorship: None availableReports 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 ExtendedStage 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