AI, Asset Management, and Ambition
In the latest episode of FinTech Focus TV, Toby Babb sits down with one of the most exciting names in FinTech innovation: Zuber Seth, Managing Partner and Co-Founder of Orchid. At only 22 years old, Zuber is already making waves in the world of asset management with an AI platform that promises to transform how funds operate. His story is a remarkable blend of youthful ambition, entrepreneurial spirit, and technological insight, all deeply relevant to the future of finance and the type of talent the FinTech industry now demands.
For Harrington Starr, a leading FinTech recruitment firm working with the most forward-thinking clients and candidates in the market, this conversation exemplifies the shift in what it means to innovate, scale, and recruit for success in today's financial technology sector. This blog summarises the full conversation between Toby and Zuber and pulls together key insights about FinTech jobs, the changing demands of asset management, and the pivotal role AI is playing in shaping tomorrow’s workforce.
Early Ambition and Building a Bloomberg Terminal for Roblox
Zuber’s path into FinTech wasn’t a conventional one. As a teenager, he spent a lot of time on Roblox, an online gaming platform with its own economy. At 16, he created a market analytics website for Roblox, effectively a Bloomberg Terminal for in-game assets. The site attracted around 13 million monthly visits, making it the most significant platform of its kind. He eventually sold it for cryptocurrency, introducing him early to trading and alternative assets.
What stands out in this story is not just Zuber’s technical ability, but his market intuition. Even as a teenager, he demonstrated the entrepreneurial thinking and risk appetite that are now essential in high-growth FinTech startups. It’s precisely this type of non-traditional background that many FinTech firms are now actively recruiting for. At Harrington Starr, we’re seeing more demand for adaptable, commercially aware talent who blend technical know-how with deep curiosity and market insight.
Skipping University to Start a Hedge Fund, and Pivoting to AI
After selling his Roblox project, Zuber began trading crypto and later equities. Rather than following a traditional academic path, he opted for a gap year to work in wealth management and hedge funds. He continued gaining experience while studying, eventually moving into quantitative research.
This experience led Zuber to try and launch a hedge fund with a bold premise: automate everything. He and his team began developing statistical and AI models to replace typical analyst workflows. With backing from the Kuwait Investment Authority, the plan was well underway until the FCA halted their application due to Zuber’s age. He was just 20.
But this setback became the foundation of something even more impactful. Rather than abandoning the tech, they repackaged it. Orchid was born, not as a fund, but as a platform to enable others to operate smarter. This pivot is a powerful example of resilience and vision. It also reflects a trend we’ve noticed at Harrington Starr: the FinTech talent of tomorrow doesn’t just follow roadmaps; they create new ones.
What Orchid Does: AI Agents for Asset Management
Orchid is an AI platform for asset managers and hedge funds. It automates analyst work across model development, research, and macroeconomic analysis. Originally, it provided tools to reduce time on repetitive tasks by 20–30 minutes a day. But over the past year, Orchid has evolved into something far more disruptive.
The latest version of Orchid eliminates its reliance on predefined agents. Instead, it dynamically constructs workflows to solve complex financial problems. When a user inputs a task, the platform assembles a bespoke “agent” to execute it, mirroring the cognitive flexibility of a human analyst. This makes Orchid not just a productivity tool, but a financial infrastructure product capable of radically transforming how discretionary funds operate.
In Zuber’s view, Orchid goes beyond SaaS. He boldly claims that “SaaS is dead,” arguing that generative AI and no-code tools have made it easy for anyone to build applications. Execution is no longer the differentiator; ideation is. The implication for FinTech recruitment is profound: businesses don’t just need developers anymore; they need systems thinkers, prompt engineers, and hybrid specialists who understand AI architecture and financial logic.
Shifting the FinTech Recruitment Landscape: What Skills Now Matter
For hiring managers in FinTech, the skills required to thrive in today’s market are undergoing a rapid shift. Orchid’s success illustrates the rising demand for individuals who can blend deep technical fluency with commercial insight. AI is automating lower-level tasks, which means the roles that remain, and the ones now emerging, are focused on direction, integration, and value creation.
Zuber’s own journey shows this clearly. He and his team have built a product capable of automating analyst workflows, but the human work remains in crafting strategy, managing clients, and pushing the product further into new markets. At Harrington Starr, we are seeing growing demand for exactly this kind of hybrid role, commercial AI leaders, technical finance specialists, and operational leads who can implement AI in real business contexts.
Compliance and operations roles are also changing. Zuber recounts his time working at the FCA, where he saw how manual processes slowed hedge fund authorisation down to a six-month slog. AI could significantly accelerate this, making compliance teams more efficient without necessarily reducing headcount. In fact, productivity gains may increase hiring in areas where time-to-market is critical.
AI and the Democratisation of Quantitative Finance
One of the most exciting themes in the discussion is how AI is democratising access to quantitative capabilities. Historically, only the largest firms, like Citadel or Renaissance Technologies, could afford the infrastructure and talent required to run complex models and high-frequency trading strategies. As Zuber notes, firms were laying their fibre optic cables just to shave milliseconds off their trades.
Orchid changes that. Smaller discretionary funds can now access AI tools previously reserved for firms with multimillion-pound tech budgets. This enables mid-sized funds to automate their research, risk modelling, and portfolio management without rebuilding their teams or systems. It’s a level playing field.
This trend is already influencing recruitment. More firms are seeking candidates who understand how to integrate AI platforms into legacy investment workflows. It’s no longer just about being able to build a model, it’s about understanding which models to trust, how to interpret them, and how to translate their outputs into investment decisions.
Why Orchid Targets Discretionary Funds, Not Quant Giants
Toby asks Zuber about Orchid’s target clients, and the answer is strategic. Rather than chasing quant hedge funds with already-automated pipelines, Orchid focuses on discretionary funds managing between £500 million and several billion. These firms rely on human analysts and often operate inefficient workflows. They’re large enough to feel the pain of inefficiency, but small enough to adopt new tools quickly.
Orchid helps these funds transition toward a more quantitative and AI-native model without needing to restructure their organisations. The platform plugs directly into existing workflows, turning manual processes into automated ones.
From a recruitment perspective, these are exactly the types of firms that need new talent strategies. As they shift from traditional to tech-enabled operations, they require employees who can operate AI platforms like Orchid, interpret outputs, and guide investment decisions. This creates new FinTech job categories, roles that blend analyst intuition with platform mastery.
The Future of Work at Orchid: Hiring for Mission, Not Comfort
One of the most memorable parts of the episode is when Toby refers to a job advert Zuber wrote for an AI engineer. It begins with a warning: “Don’t apply to this job.” It lists long hours, low startup pay, and constant challenges. But it ends with a bold invitation: “This is your life’s work.”
It’s a powerful reflection of startup reality, and a sharp contrast to the glossy founder myths often portrayed online. Zuber is candid: being a founder isn’t glamorous. There’s no clocking off. It’s long hours, high pressure, and relentless learning. But it’s also a chance to shape the future of an industry.
At Harrington Starr, we regularly partner with high-growth FinTech startups. Increasingly, we see candidates drawn to this level of mission-led work, those who want their next role to mean something. But it’s not for everyone. Zuber’s hiring strategy filters for individuals who are mission-aligned and resilient, not just CV-qualified. He’s building a team as lean and focused as the product they’re delivering.
What’s Next for Orchid: Product, Clients, and the AI Arms Race
Having recently closed a successful seed round, Orchid is now scaling. The team is releasing a major update that removes fixed agents and allows the platform to build itself around any financial task. In Zuber’s words, it will "think like a human”, breaking down a prompt and assembling the best tools to solve it.
The next 18 months will be about growth. That means onboarding new discretionary fund clients, refining the user experience, and further positioning Orchid as the AI infrastructure provider for finance. Zuber mentions that while they do work with some £100 billion+ institutions, their focus remains on mid-sized firms where the impact of AI is most immediately felt.
Recruitment will also play a role, but not in the traditional sense. Orchid believes in automating internally wherever possible. Rather than building out large departments, they plan to hire strategically for key roles. That means they need candidates who are adaptable, proactive, and fluent in emerging technology. These are exactly the types of professionals Harrington Starr specialises in sourcing for our clients.
AI and FinTech Recruitment in 2025: Insights from the Frontlines
Zuber’s appearance on FinTech Focus TV isn’t just a glimpse into the future of one company, it’s a blueprint for how the financial services industry is evolving. AI is no longer a back-office experiment or a speculative buzzword. It’s a strategic lever for growth, efficiency, and competitiveness.
For FinTech recruitment businesses like Harrington Starr, the message is clear. Clients need candidates who can bridge finance and AI. Whether it's product leaders who understand LLMs, analysts who can guide AI workflows, or compliance professionals who can partner with tech, the future of hiring is hybrid. Roles are evolving fast, and so are the skills required to succeed in them.
This episode also reinforces the importance of adaptability. As FinTech continues to attract ambitious, tech-driven founders like Zuber, businesses must be willing to hire outside of conventional boxes. University degrees are being replaced by entrepreneurial experience. Traditional job descriptions are giving way to broader mission-focused roles. Those who embrace this shift will have a distinct advantage in hiring the top 1% of FinTech talent.
Final Thoughts: The Future Belongs to the Bold
Zuber Seth is emblematic of a new generation of FinTech entrepreneurs, fearless, technically astute, and mission-driven. His story offers lessons not only in innovation and AI, but also in hiring, leadership, and resilience. For clients of Harrington Starr looking to grow, transform, or digitise their investment operations, Orchid is a signal of where the industry is heading. And for FinTech professionals looking for their next challenge, it’s a reminder that ambition, adaptability, and authenticity are the most in-demand skills of all.
To watch the full episode of FinTech Focus TV featuring Zuber Seth, Co-Founder of Orchid, head to our media hub. For expert support in finding the AI-savvy professionals your FinTech business needs, contact Harrington Starr, your trusted partner in FinTech recruitment.
