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/ After the raise
Suddenly everyone is an AI recruiter.
We’ve been one since 1999, when it was called machine learning.
The last thing you need is more resumes to review. You need people who thrive in ambiguity, move fast, work cross-functionally, and know how to build inside a startup.
The capital gives you the opportunity. The team determines what you build with it.
LinkedIn is the car alarm everyone stopped listening to.
The people you want are already employed, already building, and not answering LinkedIn InMails. So we search beyond LinkedIn, and reach them where they actually respond.
Our database isn’t the advantage. Knowing who to pursue, when to pursue, and getting them to engage, is.
More applicants won’t solve your hardest hire.
The person who changes your trajectory is eighteen months into something they care about, paid well, and working for someone they respect. No job post reaches them because they aren’t reading any. One good cold call from us might.
You don’t wait for those people to apply. You headhunt them.
Precision, not volume.
Eight candidates presented for every offer extended. Screening, calibration and reference work happen before anything reaches you, so your engineers spend interview hours evaluating people who can do the job instead of filtering out people who can’t.
Nearly nine in ten offers we take to a candidate get signed. A declined offer is the most expensive outcome in a search. We only extend once comp is calibrated and the counter-offer conversation has already happened.
A month from kickoff to a signed offer. After a raise the roadmap is already committed, and every month a senior seat sits open is a month the plan slips behind the capital.
No H-1B transfers across three years of placements. No petition to file, no premium processing fees, and no start date waiting on a receipt notice. Your offer converts on your schedule.
25+ years of building technical teams. From early internet infrastructure and ML to modern production AI.
Built personalization and recommendation teams before recommendation engines were a category.
Built the first non-founding data infrastructure and machine data team.
Built the AI org that became Einstein, and is now Agentforce.
Built the initial lakehouse, data orchestration and AI/ML infrastructure team.
This isn’t theory.
35 hires at TetraScience, from senior individual contributors through architecture leadership across distributed systems, data infrastructure and AI/ML.
Verticalmove has been an extension of our internal team from day one. No warmup required.
Ellen DiPasqualeChief Human Resources Officer, TetraScienceLet us be useful before you decide anything.
A raise creates a hiring problem and a calibration problem at the same time. Fifteen minutes, no charge, no obligation, and yours whether or not we ever work together.
Passive talent map
We run your actual role through the stack above and come back with a count. How many people in your metro have shipped this before, where they sit now, and what share have ever answered a recruiter.
Post-raise talent sequence
Tell us what you have to accomplish over the next twelve months. We’ll work backward into the capabilities, roles and hiring sequence most likely to unlock it.
Comp calibration
Live bands and equity mix for distributed systems, data engineering, ML and AI seats at your stage and metro. What a passive candidate actually resigns for, and which of your existing bands will lose a competitive process.
Startup-fit scorecard
A one-page interview scorecard for ambiguity, speed, cross-functional range and startup experience. Built so the loop stops rewarding people who interview well.
If the fit is wrong, we will say so.
None of these require a search, a contract or a budget line. If fifteen minutes tells us we are not the right firm for what you are building, that is a useful outcome and we will tell you plainly.
Send me this →Want to know what happens if you give us a search?
Four ways to engage. Clear fees. A defined process. No mystery.
See how we work →