Software Engineer (New Grad)

Maximor AI•New York City, NY

47d•Onsite

About The Position

Maximor is building the AI operating system for the CFO office. Our Audit-Ready AI Agents connect to a company's existing finance stack—ERPs, banks, billing, payroll, CRM, contracts, spreadsheets, email, and Slack—and automate the work behind the entire order-to-cash process, record-to-report process, treasury management, financial reporting, and audit readiness. The goal is for finance teams to review exceptions while AI does the rest. Maximor's difference is its Unified Finance Context, a financial understanding layer that captures transactions, policies, contracts, historical decisions, and accounting judgment. On top of it sit Audit-Ready AI Agents that can reason, explain their decisions, escalate uncertainty, and continuously improve. The company has raised $9M led by Foundation Capital, alongside BoldCap, Gaia Ventures, Aravind Srinivas (CEO of Perplexity), and finance leaders from Zuora, Ramp, Gusto, MongoDB, Zoom, and the Big Four. You will join a pod of 2–3 engineers that owns a finance domain end-to-end—revenue, cash, close, reporting, payroll, fixed assets, tax, or controls—and you'll own real surface area inside it from your first month: context, prompts, tools, evals, guardrails, and the product around them. A senior engineer pairs with you closely at the start. The expectation is that you will be scoping and shipping your own work by the end of your first quarter. You will sit with the controllers, accountants, and CFOs who do the work today, understand it properly, then build the agent system that replaces it.

Requirements

Bachelor's or master's degree in Computer Science, Machine Learning, or AI, or graduated within the past year.
Adjacent quantitative degrees are welcome if supported by work experience.
At least one substantial software engineering or AI engineering internship.
Hands-on experience building with AI agents (internship, research, coursework, or side project).
Real fluency with coding agents (Claude Code, Cursor, or equivalent).
Strong fundamentals in a modern language, preferably Python.
Something real you can walk through in depth (side project, research prototype, open-source contribution, hackathon build).

Nice To Haves

Experience at early-stage and AI-native startups.
Shipped production code at a company under 50 people.
Experience with Claude Code, Cursor, or equivalent, with opinions on when to use them.
Depth in C++, Java, Go, or Rust (if not Python).
Research in AI, ML, or systems (published or in progress at NeurIPS, ICML, ICLR, ACL, or similar).
TA'd or course-assisted a serious systems, ML, or compilers course.
Shipped a side project that real people used.
Contributed to open source that other people depend on.
Built evals, verification, or observability for something non-deterministic and caught a bug before a human did.
Interned at a pre-seed through Series B startup and thrived in ambiguity.
Done well in competitive programming or olympiads (ICPC, IMO, IPhO, Putnam, or similar).
Curiosity about fintech, accounting, or how money actually moves.

Responsibilities

Own real surface area within a finance domain end-to-end, including context, prompts, tools, evals, and guardrails.
Understand finance workflows by working directly with controllers, accountants, and CFOs.
Build AI agent systems to replace existing finance workflows.
Scope and ship your own work.
Make decisions across the LLM pipeline, infrastructure, backend, and UX.
Dig into issues until the root cause is understood when something breaks.
Use coding agents fluently to ship faster.
Build AI agents with craft in prompt and context design, tool use, and evals.
Communicate clearly, ask good questions, share progress, and indicate when stuck early.