Scaling APIs, data and model serving
Backend Engineering Recruiters for NYC AI Startups
Model calls, customer data and growth all land on your backend. The backend engineers we put forward for New York City AI startups have kept systems like yours running through rapid growth, migrations and late-night incidents.

At a glance
Backend hiring for products built on models
We recruit across backend, platform and infrastructure engineering. Most searches start with one question: what breaks first as you grow?
Roles we recruit for
Senior and staff backend, platform and infrastructure engineers
Stages
Seed to Series C
Where
New York City. In office, hybrid or remote
Who we look for
Engineers who scaled production systems and kept them up through incidents and migrations
Speed
Our last 3 hires averaged 17 days
How you pay
Retained, success-based or embedded. Terms agreed upfront
How we assess
Backend engineers who have been on call for it
Plenty of engineers have worked on a big system. We find the ones who had a part of it to themselves, changed it and answered for it when it broke.
01
Owned a system end to end
Design, deploys, on-call and roadmap. We want to know which service was theirs. Shared ownership is fine if they can name their part.
02
Scaled without a rewrite
10x growth handled with targeted changes, and a clear view on when a rewrite really was the right call.
03
Built around model calls
Queues, caching, rate limits, token and GPU costs. We ask about the backend work around model calls, which is where AI products often slow down.
04
Improved how the team builds
We ask what they changed in how the team works, such as review standards, runbooks or design docs, and whether it stuck.
Systems they owned
Scale and incidents
AI serving work
Notice and pay
System design
Code and API quality
Debugging under pressure

Who runs your search
Liam, Founder of StellarSearch
Our team brings 20+ years of search experience across engineering, AI/ML, product and GTM.
LinkedIn ↗
Client feedback
Feedback from founders and the engineers we placed



I'm not really sure how he does it, but he continues to find us top tier talent that fits exactly what we're looking for."











I'm very grateful they reached out."

Would highly recommend."

They did a great job explaining roles, companies, and interview processes and was friendly + supportive throughout."

Where our hires come from
We've placed people from teams like these
We look past titles to the work: ex-founders, early employees and people doing their best work outside the day job.




How we work
How we run your search
From the first call to an accepted offer. What we handle, and the few places we need you.
Learn what you're building, what the hire owns in the first 90 days, and the comp, equity and location you can offer.
One call with the founders.
Map the market from day one. If the problem is sourcing, pay, location, process or the profile, we tell you early.
Agree any changes to the brief.
Approach people who aren't applying anywhere, and assess each one on evidence before they reach you.
Nothing. This part is ours.
Send each candidate with our write-up, then schedule and keep the process moving.
Run your interviews.
Advise on the offer, handle the back and forth, and close.
Make the final call.
If the search isn't working, we tell you fast. We use market data to recalibrate instead of sending weaker candidates for weeks.
Ways to work with us
Three ways to work with us
Pick the model that fits the hire. All terms are agreed upfront, with no hidden fees.
Best for a priority hire
Retained
A dedicated search for the one hire that can't wait. We commit time to your role from day one.
Dedicated search from the first call
Market map shared with you
Fee agreed upfront
Best for a single hire
Success-based
We run the search and you pay when the hire is made.
No fee until you hire
Same assessment on every candidate
Terms agreed before we start
Best for several roles
Embedded
We work as part of your team across several hires, for a monthly fee plus a reduced success fee.
Monthly fee plus reduced success fee
One hiring standard across roles
Works alongside your in-house team
Start a search
Start your backend engineering search
Tell us what you're building. We'll come back with how we'd run the search.
Looking for a role? See open jobs
What does a backend engineer do at an AI startup?
A backend engineer builds and runs everything behind the product: APIs, data stores, background jobs and the services that call models. At AI companies that includes managing the latency, cost and rate limits of those model calls.
When do we need a platform engineer instead of a backend engineer?
Usually once shared tooling, such as deployment, observability and internal APIs, starts slowing every engineer down. Until then, backend engineers build the services your product runs on and handle that tooling as part of the job.
Can you find backend engineers who know our languages?
Yes. We make the language a hard requirement when the work depends on it from day one, such as tuning a high-throughput Go service or working deep in Python ML libraries. Otherwise, experience with similar systems predicts success better than the language, and we tell you which candidates would be switching.
Should we hire a backend specialist or a full-stack engineer?
If most of the work is product features, a full-stack engineer ships them end to end. Hire a backend specialist when the hard problems sit behind the API: data volume, uptime, integrations, or the cost and latency of model calls. Enterprise customers often bring that point forward.
What should a backend technical interview cover?
A design problem from your own product, like rate-limiting model calls per customer, and a debugging session based on a real past incident. Both show how a candidate works under real constraints, which puzzle rounds don't. Our write-up tells you what to focus on for each candidate.
Can a backend engineer also cover data engineering?
For simple pipelines, yes: moving product data into a warehouse or feeding a model is often part of the job. When the work becomes analytics, data quality and many sources, a data engineer is the better hire. We check how much pipeline work each candidate has owned.
How quickly will we see candidates?
We deliver exceptional candidate submissions within 24 hours, and for well-calibrated searches we can have candidates in process within the first few days, without compromising on the bar. Our last 3 hires averaged 17 days from submission to accepted offer.
We already have an in-house recruiter. Why use you?
Because the people you want usually aren't applying. Most of our clients already have founders, an internal talent team or both recruiting. We focus on the people they aren't reaching: we map the market and approach candidates who meet your real bar.
How much of the process do you own?
As much or as little as you need. At the simplest level, we source, qualify and close candidates. When we're embedded, we also help define profiles, calibrate pay, design interview processes, manage offers and advise founders on the close.
What if the search isn't working?
We tell you, fast. Because we map the market from the start, we can usually see whether the issue is sourcing, pay, location, the interview process or an unrealistic profile. We bring that data back and recalibrate instead of sending weaker candidates for weeks.
How do you charge?
We work retained, success-based or embedded, and agree everything upfront with no hidden fees. For individual searches, we offer retained or success-based terms. Higher-volume clients usually work with us embedded, for a monthly fee plus a reduced success fee. Placements are backed by a 60-day placement guarantee.
Hiring your founding team?
Tell us what you're building. We'll find the experts who can build and ship it.
Start Hiring