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DeepTech Partner
Cutting emissions inside the cement kiln
0
key hires
0
independent sourcing channels up from 1
0
%
response rate on their hardest engineering search
locations:
- UK
Overview
Cutting emissions inside the cement kiln
Cement is one of the hardest industries in the world to decarbonise. It is everywhere, it is cheap, and the chemistry that makes it releases carbon dioxide by design. Gigaton, known as Carbon Re when we embedded, builds AI that works inside that constraint, applying machine learning to plant data so producers cut fuel use and emissions in kilns that are already running.
A Series A round gave the team the money to build the next version of that promise, an AI layer sitting on top of the core product. It also gave them a hiring plan they had no way to deliver on. The roles were machine learning, solutions engineering and platform, the kind of technical hires every AI company in London was chasing at the same time.
They came to us through a referral from Planet A, one of their investors. There was no internal talent function and no appetite for agencies. In enters Bond!
No talent function to inherit
We embedded one Talent Partner into the team in September 2025 for a nine month partnership, covering technical hiring end to end alongside the founders and the COO.
The starting point was inbound only. CarbonRE had a strong name inside the climate community and very little profile in the wider engineering market, while competing for senior engineers against AI companies with bigger budgets and louder brands. Nothing was being headhunted, because nobody in the business had done it before. Candidate data sat across Polymer, spreadsheets and Slack DMs, which made funnel health impossible to read and hiring decisions a matter of instinct. So the brief was to add headhunting capability.
Challanges
- A tiny addressable market: Lead Edge was the hardest engineering role on the plan, a genuine unicorn brief.
- A bar still being defined: the founders were working out what they wanted while we searched for it. Much of the work was market education, then agreeing where the brief had to move.
- Competing against AI giants: for the same ML and platform engineers, without the budget or the name recognition.
- No single source of truth: reporting was near impossible before the data moved.
The hires
8 hires across 6 divisions. The function had to flex between deep tech, volume technical hiring and a commercial-engineering hybrid, one Talent Partner covering all of it.
- Machine Learning Engineer (x2)
- Software Engineer, Enablement (x2)
- Solutions Engineer (x2)
- Deployment Manager
Two further offers were live at the point of handover, both sourced through the referral scheme we built.
Building the channels, not just the pipeline
We took on the project work CarbonRE needed to scale sustainably across three markets:
We delivered project work to leave lasting value:
- Ashby ATS migration: the full move from Polymer, run single-handedly alongside live searches. Every number in this story comes from the clean data the team now owns.
- Referral scheme: built from scratch, with eligibility rules, rewards and a submission flow through Ashby. Referrals had been happening over Slack and getting lost.
- Candidate experience and outreach: personalised InMail tied to individual career arcs, mission framing tested across roles, and warm declines that keep people in the network. The 71.4% response rate on Lead Edge is the proof.
- Onboarding their first talent hire: we brought CarbonRE’s own talent person into the function we had built, so the handover was a continuation rather than a restart.
Together we achieved
- 8 hires from 12 offers, with 2 more live at handover, taking the company past 30 people
- 4 independent sourcing channels at handover, up from 1: headhunting 5, referral 2, ATS talent pool 1, events and community 1
- 25% of hires through a referral scheme that did not exist nine months earlier
- 71.4% response rate on their hardest engineering search, against a 33% platform benchmark
- CV to first interview conversion up from 58% to 78% between September and March
