Maximor AI — Staff AI Engineer

Type: Full-time | On-site | New York City, NY Compensation: $200,000–$250,000 + 0.1%–0.35% equity Hiring count: 1 Visa sponsorship: None Available Reports to: Founding engineering team

About Maximor AI

Maximor is building the AI operating system for the CFO office — connecting to a company's existing finance stack and automating the work behind the close, revenue recognition, reporting, cash management, and audit readiness. The goal isn't to help accountants write better prompts; it's for finance teams to review exceptions while audit-ready agents reason, explain their decisions, escalate uncertainty, and continuously improve. The company has raised $9M led by Foundation Capital, alongside Aravind Srinivas (CEO of Perplexity) and finance leaders from Ramp, Gusto, Zuora, and the Big Four.

Founded: 2023 | Team size: 1–10 (Seed) | Total funding: $9M Industry: AI Tools / Fintech Website: https://maximor.ai Office: New York City, NY

Why Candidates Should Join

• Org-wide leverage, not module ownership: Own the platform layer every engineering pod builds on — your work multiplies the output of the entire team.
• Strong seed backing: $9M led by Foundation Capital, with the CEO of Perplexity and senior finance leaders from Ramp, Gusto, Zuora, and the Big Four behind them.
• Ground-floor abstraction design: Define the agent harness, financial context graph, and verification standards that determine whether AI is safe enough to touch a customer's books.

The Role

Maximor is hiring a Staff AI Engineer to own the platform layer that every engineering pod builds on — from agent frameworks and context systems to orchestration, verification, observability, and data infrastructure. This is not a module-ownership role; the work multiplies the output of the entire engineering team, and the person is expected to identify the bottlenecks limiting the company rather than wait for specs from a PM or an architecture committee.

What You'll Be Doing

• Own the agent harness the entire company builds on — abstractions for context, verification, guardrails, observability, and developer tooling so every pod ships audit-grade AI agents on shared rails.
• Design and build the financial context graph: the structured layer every agent reasons over (ledger state, policies, contracts, precedent, entitlements) kept coherent, scalable, and multi-tenant safe.
• Define the verification, auditability, evals, and observability standards that decide whether AI output is safe enough for a customer's books — and enforce them by construction.
• Own the ingestion, normalization, reconciliation, and canonical ledger model that turns ERP, bank, billing, payroll, CRM, and email data into a trustworthy source of truth.
• Design the durable execution layer for long-running AI workflows and the exactly-once, audit-ready path that safely writes back to ERPs and systems of record.
• Build architectural primitives and frameworks that become the foundation other engineers depend on, compounding leverage across the org over time.

Tech stack: Python (primary), agent frameworks, distributed systems, workflow/transactional engines, data infrastructure. Fluent AI-coding-agent use (Claude, Cursor) valued.

Requirements

• 2 or more years of agentic AI work, research-oriented background
• 8 or more years software engineering, distributed systems or platform depth
• Platform-layer experience, multiplied output across engineering teams
• Early-stage startup experience, pre-seed through Series B
• NYC in-person
• Startup hours, 6 days a week, 9am to 7pm or 8pm

Green Flags

• Deep agentic AI experience with architectural ownership
• Research-oriented ML or NLP background applied to production
• Prior Staff or Principal IC at a high-growth startup
• Finance, ERP, audit, or compliance domain background

Red Flags

• Frontend-heavy profile without meaningful backend or systems depth
• Tool-list resume without substantive project or architectural detail
• Several short job stints without clear context
• Needs a defined scope or structured environment to operate

Role Details

• Salary — $200,000–$250,000
• Equity — 0.1%–0.35%
• On-site policy — In-person at the NYC office; startup hours, 6 days a week, 9am–7pm/8pm
• Visa sponsorship — None Available
• Employment type — Full-time
• Location — New York City, NY

Benefits & Perks

• Full medical, dental, and vision for employees and dependents
• 401k with employer match
• 0.1% to 0.35% equity
• Meals and stocked NYC office

Interview Process

Stage 1 — Pending Approval — Candidates awaiting initial approval. Stage 2 — Founding Engineer Screen — Screen with the founding engineering team. Stage 3 — Take-home Assignment (5–8 hours) — Practical build task. Stage 4 — Take-home Debrief — Walk through the submission. Stage 5 — On-site (5–6 hours) — Full on-site loop. Stage 6 — Offer Extended Stage 7 — Candidate Hired — Candidate accepts and starts.

Notes

• Intake Call Summary, Screening Questions, Ideal Companies, Ideal Candidate Profiles, and Rejected Candidate Feedback were not present on the role page — none captured for this role yet.
• Scoring note (experience Requirements): two experience floors here — 2+ years agentic AI and 8+ years overall SWE. Out-of-band experience is a scaled Red Flag, not a rule-out; every other Requirement operates as a hard rule-out unless David overrides.