TLDR;

- Slate is the AI-native lending platform used by Australian lenders, with AI built into the product credit teams use every day.
- You'll own a product domain end to end: decide what to build with the people who use it, build it with AI, and stand behind its quality.
- AI-first from day one. Agents are part of how we build, and you're the one who makes sure what ships is right.
- Small team, low overhead, real influence on the roadmap. Still early enough to shape the product and the culture.
- Backed by leading Australian and international investors, including Square Peg, NAB and CBA.

About Slate

Assessing a home loan in Australia still means a credit analyst spending hours working through payslips, bank statements and policy PDFs by hand. They recalculate hours times hourly rate against a payslip, re-annualise income the system already has, and jump between screens to piece one application together. Loans take weeks when the decision could take minutes.

Slate is the lending platform that fixes this. We turn credit policy into executable code, pull structured data out of messy documents, and put AI to work alongside credit teams. AI does the triage and collation; every credit decision stays explainable and auditable, with a human accountable for it.

The Role

As a Founding Engineer, you'll own a product domain, and stay with it long enough to have real opinions about it. Owning it means deciding what to build as much as building it, and seeing how policy, data, agents and people fit together as a system. You'll sit with credit analysts and brokers, shape the roadmap, design the experience, ship it and run it in production.

Engineers here help decide what gets built rather than waiting on a spec. Alongside building, some of your week will go to time with users, scoping problems and testing what shipped. The balance shifts with what your domain needs.

How you'll work with AI

We work with AI agents every day. Our code generation and review pipelines are established, with room to bring your own tools. Your craft is decomposition, verification and taste: breaking problems down, proving the solution works, and judging what's worth shipping. When an agent gets something wrong, you fix the harness so it gets it right next time. In lending, "looks right" isn't enough, accuracy is critical. Some of the problems you'll work on:

- Benchmarks that make our agents measurably better.



Working out what's verifiable in a credit decision and making it measurable.
- AI that stays explainable and auditable, because lenders and regulators need to see exactly how every credit decision was made.
- Verified data from messy documents. Payslips, bank statements and tax returns turned into figures an analyst can trust.
- Agents and policy rules working together. Designing how AI investigates an application while deterministic credit rules keep it grounded.

What You'll Build

- The credit assessment experience. A clear workflow that tells analysts what needs their judgement and does the arithmetic for them.
- AI that works alongside credit teams. Agents that review applications, check documents, flag inconsistencies and draft what's needed from brokers, with evals you'd trust on a lending decision.
- Credit decision engines. Serviceability, product eligibility and policy rules as executable, testable code.
- Document extraction. Payslips, bank statements and tax documents turned into structured, verified data.
- Broker and lender experiences. The portals brokers submit through and lenders operate in.
- Loan servicing (our Loan Management System). The system that runs loans after settlement: repayment schedules, payments, reconciliation, statements and alerts. It services our own loan book today, with room to grow into a servicing platform for other lenders.

Who We're Looking For

This role suits engineers who enjoy shaping what gets built as much as building it. If you want to own a product, understand users and ship what they need, let's talk!

Mindset

- Product-minded. You're comfortable spending time with users, on scope and on testing, not only in the code. You have taste in UX and own the quality of the UI you ship.
- Comfortable with ambiguity. Give you a messy problem and you'll break it down, decide what to build and make the calls without hand-holding.
- AI-fluent, quality-obsessed. You get leverage from agents, verify what they produce properly, and improve the system when they get it wrong.



You manage agents but own the outcomes.
- High ownership. You don't walk past problems, your default is to grab issues you spot and see them through to a complete resolution every time.
- Love a complex domain. You enjoy getting to the bottom of intricate scenarios, and you'll go deep enough to hold your own with the experts who use what you build. Here, that means lending: credit policy, payments and regulation.
- Pragmatic in a regulated world. You ship small and fast, while respecting the controls a lender needs.

Essential experience

- 5+ years building and shipping production software, owning features end to end
- Comfortable across the stack, especially contemporary TypeScript/React frontends
- A track record of shipping product real users rely on, ideally at a startup
- Hands-on experience building with AI coding agents day to day

Preferred experience

- Lending, payments, fintech or another regulated industry
- Product management, or taking your own product to market
- Building LLM-powered product features: agents, evals, benchmarks, document extraction
- Harness engineering: making codebases work well for agents
- PostgreSQL and Kotlin/Spring

Why Join Slate?

- AI that real people depend on. Most AI products are still demos. Ours helps credit teams make lending decisions today, and we think we're ahead of anyone in Australian lending.
- AI-first. You'll build with the best AI tooling from day one.
- Real influence. As one of our early engineers, you'll shape the roadmap, technical direction and engineering culture.
- Impact you can see. Your work cuts loan processing from weeks to minutes and helps Australians get into their own home sooner.
- Growth. A $2,000 annual learning budget, and support to speak at fintech meetups and conferences.

Hiring Process

1. Phone screen with Bridget: who you are, what you've built and what you're looking for.
2. Case study (in person) with two of our engineers: a realistic problem from our world, such as turning a piece of credit policy into a feature. You'll scope it, decide what to build and show how you'd know it works. We tailor it to your strengths.
3. Final chat with James, our CEO (in person)

How To Apply

Send us your LinkedIn/CV and a link to the product or project you're most proud of. Tell us what problem it solved, how you decided what to build, and where you went above and beyond.

📌 Founding Engineer (Sydney)
🏢 Slate
📍 Sydney