Fleek appoints head of talent

Online wholesale platform Fleek has appointed Matthew Parker as its founding head of talent as it scales its London team.

The hire supports the company’s growth and its AI-first operating model, with recruitment underway across engineering, product, commercial and operations roles.

Matthew will be responsible for building Fleek’s people function from the ground up, with a focus on attracting “AI-first operators” who combine commercial thinking, technical expertise and strong execution.

He will also lead hiring strategy to support Fleek’s technology aimed at modernising the global secondhand fashion supply chain.

Matthew said: “People who have used the most advanced tools already think differently about their careers.

“They’re already asking themselves what their role will look like in two years.

“We’re giving candidates access to tools like Claude Code during the interview process so we don’t exclude people who simply haven’t had the opportunity to use them yet. 

“We want to find the right people, not just the most privileged.”

The appointment comes as Fleek continues to expand its platform, connecting thousands of resellers worldwide and supporting the growth of the circular fashion economy.

Alberto Lo Bue, vice president of growth at Fleek, added: “The fashion industry produces over 100 billion garments a year, and around 60 per cent end up in landfill, not because people don’t want these clothes, but because the infrastructure that moves secondhand fashion from donation to resale is still largely offline.

“Fleek is fixing this.”

“The real skill is recognising when AI output is good enough versus when it’s confidently wrong. 

“That analytical rigour is what separates exceptional operators.”

“AI is splitting the analyst role in two. 

“Execution is being automated, while problem framing, interpretation and decision support are becoming even more important.”

Co-founder Sanket Agarwal added: “In an AI-native world, internal operations become a collection of agents and tools with humans in the loop. 

“Our teams are already building internal tools connected to our data in minutes rather than waiting on engineering.”

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