When QED Investors, Blackbird, Square Peg and Airtree all back the same early-stage Australian AI startup, the funding round is news. What matters more for anyone hiring or being hired in fintech right now is why they all said yes, and what the founder behind it says about building and hiring in an AI native company from the ground up.
Steve Hind, co-founder and CEO of Lorikeet, joined me on Fintech Chatter after closing more than $50 million USD in funding, the first time since Canva that all three of Australia's top venture firms have backed a company at this stage. What he shared about the decade of experience he brought into founding Lorikeet, across BCG, Bridgewater Associates, Stripe and climate tech company Watershed, is some of the most useful thinking on fintech hiring and AI native leadership I've heard on the show.
Lorikeet builds AI concierges for high-complexity, high-regulation businesses in financial services, healthcare and energy. The platform handles customer interactions across phone, chat, SMS and email, 24 hours a day, and is designed to resolve problems rather than deflect them to a FAQ page or a human queue.
The distinction matters for fintech recruitment and AI adoption alike. Most AI customer support tools were built for simple SaaS or e-commerce businesses. Lorikeet was built from the start for businesses where the wrong answer carries real risk: regulated financial products, sensitive health data, compliance obligations across multiple jurisdictions. Customers include Airwallex, Linktree and Eucalyptus, the Australian telehealth business recently acquired by Hims & Hers in a deal valued at up to $1.15 billion.
Co-founder Jamie Hall, who ran LLM research at Google Brain before leaving to build with Steve, is the architecture behind why Lorikeet works where off-the-shelf AI tools don't. Rather than taking an existing model and wrapping it, Hall and Hind built their own architecture for the specific requirements of regulated industries, one that can take actions, follow standard operating procedures and apply judgement in a way that a knowledge-base chatbot cannot.
Steve spent several years at Stripe in product roles during a period of rapid headcount growth. He ran hundreds of interviews, focused heavily on hiring product managers, and saw what it looks like when every qualified candidate in the market wants to work for you. It is, by his account, the opposite problem to the one he faces at Lorikeet.
At Stripe, the work was filtering: everyone with an impeccable CV was applying, so the challenge was finding the genuinely good ones inside a very large pool. At an AI native startup like Lorikeet, the candidates with the best CVs have no shortage of offers, including from frontier AI labs like Anthropic and OpenAI. The only way to win them is to offer something the market at large won't: a role with a scope they wouldn't get elsewhere, a technology bet they want to be part of, or a career step the obvious employers won't give them yet.
His framework for fintech hiring at startup stage: find people who need this role to work out, not people who can afford for it to go either way. Mutual alignment is the foundation, not the nice-to-have. If a candidate doesn't need your company to succeed for their career to go where they want it to go, you will never get the commitment and ownership the role requires. This is a lesson that applies directly to fintech recruitment across the board, not just AI native companies.
Hind's path into fintech and AI is not linear. He started at BCG, moved to Bridgewater Associates, completed an MBA at Harvard Business School, joined Stripe, then went to Watershed before founding Lorikeet. He is explicit that if he had known what he wanted to do earlier, the detours would have been costly. Because he didn't, they compounded.
BCG gave him what he calls an excellent apprenticeship in structured thinking and problem solving. It also taught him what he didn't want: the frustration of generating recommendations he never got to implement. That push toward execution rather than advice is visible in how Lorikeet operates, and in how Hind describes the leaders he wants to hire.
Bridgewater is where the operating principles came from. The culture demands obsessive focus on what is true rather than being right, and a low ego approach to feedback that is easier to describe than to practise. For fintech executives and board members evaluating AI native leadership candidates, these are the qualities that separate people who can function in a high-uncertainty environment from those who can only operate off a defined playbook. Fintech and AI are both fields where the playbook is being rewritten faster than most people can read it.
One of the most direct statements Hind made on Fintech Chatter is worth quoting in full for anyone in fintech recruitment or building a leadership team in 2026: if your leaders are not personally and actively using frontier AI tools in their day-to-day work, they cannot coach their teams effectively. They don't know what's possible, they can't challenge timelines or estimates with any accuracy, and they're running a 2021 playbook in a 2026 environment.
For fintech and financial services businesses hiring senior leaders right now, that is a filtering question, not a preference. A chief operating officer, chief product officer or chief compliance officer who has not built personal fluency with AI tools is carrying a material capability gap. The AI native era has changed what every leadership role requires, not just the technology roles.
Hind is also specific about what AI native does not mean at leadership level. It is not about removing experience. It is about being able to tell which parts of accumulated experience still apply and which parts are now obsolete, and being honest about the difference. The leaders who can't make that distinction will, in his view, get left behind regardless of how strong their prior track record is.
One of Lorikeet's differentiators is that it built for regulated industries first rather than treating compliance as a constraint to work around later. Operating across financial services, healthcare and energy meant building a single architecture capable of meeting the requirements of multiple regulatory environments, an approach that has proved more scalable than building bespoke solutions for each client.
The compliance observation that resonates most from Hind's conversation is also the most counterintuitive: AI, when built correctly, is already more rule-consistent and auditable than human agents. Policy changes propagate instantly rather than going through a retraining cycle. Every decision can be logged and its reasoning made explicit. Consistency doesn't degrade with volume, time of day or workload.
For fintech recruitment, this reshapes what a head of compliance or chief risk officer actually needs to be in 2026. The tick-and-bash compliance professional is being displaced by AI doing the rules-based work consistently and at scale. The compliance leaders who are thriving are the ones who have become more commercial and more creative, able to set intelligent guardrails rather than just enforce existing ones. They are also, as Hind notes, rarer. The supply of that profile has not kept pace with fintech demand, and it shows up every time a client calls Tier One People with a compliance brief.
Lorikeet's $50 million USD raise, led by QED Investors with Blackbird, Square Peg and Airtree all participating, is notable for two reasons beyond the dollar figure. First, it is the largest early-stage consensus among Australian venture funds since Canva. Second, QED Investors is the leading global fintech VC fund, and their investment signals that Lorikeet is being evaluated against a global peer set, not just the Australian AI startup market.
For fintech recruitment and talent attraction, that backing matters in practical terms. It signals to senior candidates that the business has the institutional credibility and capital runway to support a serious career move. It also signals to the market that AI native fintech infrastructure is a category worth building careers in, not a hype cycle to wait out.
Airwallex, one of Australia's most recognised fintech success stories and a Lorikeet customer, is a useful data point here. Fintech talent in Australia has watched Airwallex scale from a payments startup to a global platform. The same arc is available in AI native infrastructure, and Lorikeet is one of the earliest credible entrants in that space in this market.
The Fintech Chatter conversation with Steve Hind covers a lot of ground, but the talent and hiring signal running through all of it is consistent: the gap between founders and executives who understand AI native operating models and those who don't is widening, and it's widening fast.
At Tier One People, the briefs we're seeing in fintech recruitment are reflecting this. Clients are asking for leaders who have built or operated inside AI native environments, not just leaders who are open to AI. The two are not the same profile. Fintech companies that are still hiring for the former profile when they need the latter are going to lose time and ground to the ones who are calibrating their search correctly.
If you're building a fintech leadership team in 2026, or if you're a senior fintech executive thinking about your next move, the Lorikeet story is worth studying closely. The $50 million is the headline. The operating philosophy sitting behind it is the more useful thing to understand.
Steve Hind, co-founder and CEO of Lorikeet, on raising $50 million USD, hiring for an AI native startup, and what BCG, Bridgewater and Stripe taught him about building.
00:00 Introduction
01:32 Understanding Lorikeet and Its AI Concierge Solutions
05:54 The Origin of Lorikeet and Its Founding Story
09:50 Navigating the AI Landscape and Company Growth
12:49 Regulatory Challenges in FinTech and AI Compliance
15:12 The Role of AI in Compliance and Customer Relationships
20:03 Steve's Career Journey and Lessons Learned
23:51 The Art of Startup Hiring
28:34 Navigating AI's Impact on Work
33:36 The Future of Work and Leadership
39:05 Optimism in the Age of AI
41:57 Advice for Aspiring Founders
What we discuss
Links
This show is brought to you by Tier One People, where we work with founders like Steve to find the 1% who redefine what's possible. If you're scaling your fintech leadership team, start at tieronepeople.com.
About Tier One People
Tier One People is Australia's specialist executive search firm for fintech, banking and the digital economy. We find the 1% who redefine what's possible. If you're upscaling your leadership team connect with Dexter Cousins at tieronepeople.com.
Fintech Chatter is Australia's longest-running fintech podcast, hosted by Dexter Cousins. 350+ episodes, 30,000 monthly listeners across 40 countries.
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