About Lorikeet Lorikeet is the most powerful customer support AI for complex businesses — fintechs, healthtechs, marketplaces, and delivery services. We're building from the ground up on the premise that most support responses should be automated with transparent, customizable AI, and that support teams should spend their time managing automation and engaging with complex cases — not grinding through high volumes of simple tickets. Once teams are freed from reactive support, we want to help them tackle what's next: delivering personalized, concierge-level service to their customers. To pull this off, we're drawing on Jamie's experience as an early member of Google's generative AI team, Steve's experience building for operational teams at Stripe, and a broader team that's come from Stripe, Canva, Atlassian, Dropbox, and Dovetail. We're growing fast, have paying customers, real revenue, and a strong pipeline. We've raised over USD $50M from leading VCs and angels including QED, Blackbird, Square Peg, Claire Hughes Johnson (ex-Stripe COO), Cristina Cordova (Linear COO), Bob Van Winden (Stripe Head of Support), and Cos Nicolaescu (Brex CTO). Our global customers include the largest telehealth company in Australia, the largest bank for teens in the US, one of the largest NFT marketplaces by trading volume, one of the largest Web3 gaming companies — and a handful of other enterprise customers processing over 1 million support tickets a year. What's unique about this opportunity Technical founders and an engineering-led culture. Everyone at Lorikeet owns working with our users and building a great product for them. Engineers take on challenging problems, define solutions, and ship them — end to end, increasingly through agent-assisted workflows. We build at the frontier. Coding agents are central to how we work — they're doing a meaningful share of our coding. That doesn't mean pushing a button and shipping whatever comes out. It means exercising strong engineering judgment: knowing how to prompt well, iterate fast, set up the right feedback loops (tests, linters, context systems), and catch what the agent missed before it hits production. If you've built features end-to-end through agent conversation — prompting, reviewing, iterating, shipping — you'll feel at home here. On the technical cutting edge. With our users, we're defining what an AI-first SaaS product looks like. No one has figured out the UI/UX, capabilities, and data models of an AI-first company — it's white space for us to invent. The agent problems we're solving go beyond the cutting edge at the biggest research labs. Our stack is TypeScript, React/Remix, PrismaORM, NestJS, and some Python. Knowledge of the stack is nice; we know good engineers pick things up fast. Warm, mature, in-person, flexible culture. Low ego, high trust. No tolerance for talented jerks. We default to working together in our Surry Hills office. People on the team have young families, so we embrace working efficiently and flexibly to fit life outside of work. We're committed to building a diverse team and strongly encourage people from underrepresented backgrounds to reach out — we value user obsession and eagerness to learn over traditional credentials. High pay, high expectations, high performance. Engineers are generally underpaid in Sydney and undercompensated with equity. We aim to match unicorn/scale-up base salaries and offer a potentially life-changing equity stake. Our team gets the same monthly investor updates we send to our backers — because they're investors and owners too. About the role You'll be building something that's genuinely innovating the world of customer support. Together we'll be defining what AI-first product development looks like in practice — the UI/UX, the capabilities, the data models. It's a wide open problem space. Day to day, you'll take ownership of hard problems from idea to production. That means working closely with coding agents as a core part of your workflow, building the tooling and feedback systems that make them effective, and bringing the engineering judgment to know when the output is ready to ship — and when it isn't. We'd love to talk if you Have 2–5 years of experience shipping code at a startup or company with high engineering standards Are excited to work with a top-calibre team on genuinely novel AI problems Are comfortable working with coding agents as a core part of how you build — not just as autocomplete, but as a real development workflow Are looking for a career-defining opportunity to grow rapidly with a fast-moving company If you're from an underrepresented background and don't tick every box, please reach out anyway! We know firsthand that diverse teams perform better, and we're proud that our team reflects a broad spectrum of identities and lived experiences. How we hire Our process is straightforward: informal chats with the team to share our pitch and understand your goals, a take-home test, and then a paid two-day work trial where you come in and ship with us. There's no better way to figure out if we work well together than to actually work together. We do ask that candidates come to the work trial ready to build in an agent-first way — taking a feature from idea to PR primarily through agent conversation. If you're still building toward that, we'd encourage you to experiment (at work or through side projects) and come back when you feel ready. We'd rather you do your best work than rush the process.