The brief
The client had raised a Series B round and needed to build its technical organisation quickly. It had no internal recruiter, limited employer brand and direct competition from larger AI businesses with more cash and more visibility.
The founders wanted to avoid a volume agency process. They wanted a small number of well-assessed candidates and a clear view of what the market would and would not give them.
What we did
We built the role scorecards with the founders, starting with the staff engineer and head of machine learning roles. We then ran a direct-scouting campaign across applied AI, platform engineering and product.
We approached 140 people directly. Of those, 70% had not been looking when we first spoke to them. We ran structured technical interviews and work-sample reviews, and gave the founders a written calibration note after each shortlist.
We also helped with the candidate pack, the interview process and the offer conversations. The client made the decisions; we made sure they had the evidence to make them.
The outcome
The client made 20 technical hires in 18 months across machine learning, platform, backend and product. Seventy per cent were direct-scouted. Twelve-month retention was 90%.
The business raised its Series C eight months after the final hire.
What the client said
“They gave us a credible view of the market when we had no employer brand. That changed the conversations we were able to have with candidates.”
— Founder & CTO, AI scale-up