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Hiring in web3, where LinkedIn does not work
Six senior hires at a crypto risk company in New York, every package above $100k, and not one of them found the way recruiters normally find people.
6Hires, all permanent placements
$150k+Typical package placed, highest $185k
0Of them sourced on LinkedInTL;DR
- Who. Chaos Labs, a New York company building financial AI and risk products for decentralised finance. Its risk systems, vaults and oracles secure value across major protocols. Founded by Omer Goldberg, backed by Haun Ventures, Galaxy, PayPal Ventures and Slow Ventures, and it raised a $55M Series A after a $20M seed.
- What they needed. Researchers, data scientists, DeFi market analysts and engineers who understand crypto markets from the inside. Distributed between New York and Israel, paid between $150k and $250k, and interviewed by five people ending with the CEO.
- Why it was hard. The people who can do this work are not on LinkedIn in any useful sense. They are on X and in crypto-native communities, they are sceptical of recruiters by default, and they judge whoever approaches them on whether that person actually belongs in the space.
- What we did. We went in through a partner who is genuinely part of that community, sources from inside it rather than from a database, and has enough standing there to get a reply. He proposed people to Chaos Labs proactively, sometimes for roles that did not exist yet.
- What happened. Six permanent placements, every one above $100k, most above $150k and the highest at $185k. We also ran the conventional playbook on four searches, contacted 311 people through it, and learned that in this market it does not work.
About Chaos Labs
Chaos Labs builds financial AI products for decentralised finance. Its platform turns market data into real-time risk intelligence, and its risk systems, vaults and oracles sit behind leading protocols, securing value at very large scale. It is headquartered in New York with a significant presence in Israel, and was founded by Omer Goldberg in 2021.
It raised a $20M seed led by Galaxy and PayPal Ventures, then a $55M Series A led by Haun Ventures. That funding is what made the compensation possible: the researcher and data scientist briefs we worked ran from $150k to $250k depending on seniority.
They came to us sideways. A partner of ours who works in crypto recommended someone from his own network for a role at Chaos Labs. That person was hired and we were paid nothing for it. It was the introduction, and the agreement followed.
The brief
Find senior people who can reason about crypto markets and risk: researchers who work directly with protocol clients, data scientists, DeFi market analysts, and engineers building oracles. Distributed across US and Israel time zones, permanent placements only, at packages a New York company with a $55M Series A is willing to pay.
The 4 problems we had to solve
Problem #1: “The people we need are not really on LinkedIn.”
This is the whole problem, and it is easy to underestimate. Crypto-native engineers and researchers often do not maintain a LinkedIn presence worth searching, because that is not where their reputation lives. Their track record is in the protocols they have worked on and the communities they are known in.
What we did
We ran the conventional playbook first, properly, so this is not a theory. Across four searches, DeFi Market Analyst, Full-Stack Engineer for Oracles, Researcher and Senior Data Scientist, we contacted 311 people on LinkedIn and by email, and hand-mapped 29 target companies. It is a competent piece of sourcing and it is not how any of the hires happened. Every placement came through crypto-native channels instead: a partner’s own network, and the platforms where people in that space actually publish what they have built.
Problem #2: “A recruiter with no standing here gets ignored.”
Even having found the right person, reaching them is a separate problem. In crypto the default assumption about an unknown account is that it is noise, and a new profile with no history behind it is not going to get a reply, however good the role is.
What we did
We went in through somebody the community already knows. Our web3 partner has a real following and a real history in the space, so a message from him is read as coming from a peer rather than from an agency. That is not a technique that can be copied quickly, which is exactly why it is worth something. It is also the reason we could talk to people who would not have answered us under our own name.
Problem #3: “Very high pay, and a bar to match.”
Chaos Labs pays at the top of the market and interviews accordingly. The researcher and data scientist process ran to five stages: the R&D manager, a technical interview with the chief data scientist, a second technical with the head of financial research, a cultural interview with the CEO, and an HR interview. Sending a plausible candidate into that is expensive for everyone.
What we did
We filtered on two axes before proposing anyone: whether they were genuinely strong technically, and whether they had worked somewhere close enough to Chaos Labs in product or business model to be credible in that conversation. Previous experience at a comparable protocol or exchange was treated as close to a requirement rather than a bonus. Packages placed ran from $120k to $185k.
Problem #4: “The right person appears before the role does.”
In a market this small, waiting for a brief means missing people. The best candidates in crypto are not applying, they are simply visible for a moment, and by the time a role is written and opened they have gone somewhere else.
What we did
We proposed people whether or not a role was open. When our partner saw somebody in his network who fit Chaos Labs technically and culturally, he introduced them proactively, and Chaos hired several people that way for roles that did not formally exist. It works only because they were funded and had the headroom to say yes, and because the introductions were selective enough that they were worth reading.
How we actually ran it
- Sourcing inside crypto-native channels, not databases. A partner’s own network, plus the platforms where people in the space publish the protocols and projects they have worked on. Almost no LinkedIn.
- A filter on two axes before anything is proposed. Technical level, and whether the person has worked on a product or business close enough to Chaos Labs to hold the conversation. Both, not either.
- Proactive introductions, open role or not. When the fit was obvious, the person was proposed anyway. Several hires came from roles that did not exist until the candidate did.
- A written intake when there was a role. Product, hiring manager, seniority, band, time zone, the interview loop with a named owner per stage, and examples of people already in the company who would be a good fit.
- Then their process, which is long. Up to five stages for research and data roles, ending with the CEO and an HR interview. Our job was to make sure nobody entered it who could not finish it.
What Chaos Labs ended up with
Six permanent hires in a market where conventional sourcing produced none.
Access to a candidate pool most recruiters cannot reach, through a partner the community already trusts.
Packages from $120k to $185k filled, against briefs banded at $150k to $250k.
Candidates pre-filtered for protocol-relevant background, not just technical level, so a five-stage process was not wasted.
Introductions to people they would not otherwise have seen, including hires for roles they had not opened.
