About Maxima

Nobody went into accounting to spend the first week of every month matching transactions by hand. Maxima was built so they don't have to. Our agents do the accounting work itself: journal entries, transaction matching, reconciliations, and flux analysis, continuously and with a full audit trail. Accountants review and approve. Nothing posts without a person signing off. We remove the grind, not the human.

Maxima is the agentic AI platform for enterprise accounting. Our three co-founders scaled finance at Rubrik from $5M ARR to a $15B NYSE IPO, built the reconciliation and billing systems behind Netflix's $32B in annual revenue, and built AI infrastructure serving two billion monthly users at Meta. We've raised $41M from Redpoint Ventures, Kleiner Perkins and Audacious Ventures, joined by former BlackLine executives and the CFOs of Rubrik and Vanta. To date we've processed more than $400B across 350M transactions at 100.00% accuracy, for customers including Scale AI, Rippling, Glean, Zendesk, Handshake, Zip, and Decagon.

We're early and moving fast. The playbook here gets written, not inherited, and the person closest to the work makes the call. We're looking for people who build from first principles and hold themselves accountable for what actually lands — people who'd rather build the category than join it. Everything you need to know is below.

The role

We are working on some of the hardest problems in enterprise automation, with an engineering team that includes staff-level talent from Robinhood, Glean, Google, Netflix, and Meta. The system handles high-volume financial data and complex accounting workflows, and every execution has to be accurate and reliable, because the output is a company's books.

Every accounting workflow and every agent at Maxima runs on the data platform, and you will build it. Financial data arrives from ERPs, banks, payroll, and billing systems in volumes that grow with every customer, and it has to be ingested, matched, and reconciled without losing a cent or a trail. As a Data Infrastructure Software Engineer, you will design and scale the systems that do that: our data lakes, our multi-tenant relational databases, and the search and vector infrastructure that supports the workflows on top.

This is a foundational role on a small team, with the ownership that comes with it. The decisions you make about how financial data is modeled, stored, and served will shape what the agents can do for years.

What you'll do

Architect our data lakes and the ingestion pipelines that feed them from ERPs, banks, and other financial systems

Build and scale our multi-tenant relational databases and the data models behind journal entries, reconciliations, and transaction matching

Evaluate and build the right search engine and vector database setup to support agent and accounting workflows

Design durable, highly available financial data processing layers that the agents depend on

Own the reliability, observability, and performance of the data platform as customer volume grows

Work with the AI Agents and product engineering teams so the platform serves what they are building

What we're looking for

5 or more years working with data systems at high-growth companies

Strong experience with relational databases and data modeling

Experience building and operating data pipelines and distributed, data-intensive systems

Familiarity with web development and cloud infrastructure such as GCP

Care about correctness; you have worked on systems where the numbers have to be right

Strong communication and collaboration skills

Nice to have

Experience with mission-critical systems such as fintech, or complex workflow engines

Search engines or vector databases in production

Financial data specifically: ERP integrations (NetSuite, SAP, Oracle, Workday), banking data, or accounting systems

Go, TypeScript, or Python

Where and how you'll work

This role is based in our San Mateo office. We value in-person collaboration and are in office four to five days a week for our on-site roles.