The AI Talent Agency for US AI and Infrastructure Companies

Ask a Founder in San Francisco where the AI talent is and they will tell you it is on their doorstep. Ask a Founder in New York, Austin or Boston the same question and you get a very different answer.

Both are right. That is the problem.

The United States does not have one AI talent market. It has several, sitting on top of each other, with different compensation bands, different candidate motivations and different working definitions of what senior means.

Vector is an AI talent agency for early-stage AI and infrastructure companies in the US, working from Seed through Series B and building technical and go-to-market teams as a single hiring plan rather than two disconnected ones.

The hard part is rarely finding people. It is knowing which people a company at this stage can actually hire, and in what order.

 

Why “AI Talent” Is Not One Talent Pool

The phrase covers at least four groups who share almost nothing beyond an industry label.

There is research talent, who move for problems and for the people they will sit next to. There is Infrastructure and Platform Engineering, who move for scale and for systems that are genuinely hard. There is Applied and Product Engineering, who move for shipping speed and ownership. And there is Go-To-Market, who move for a market they believe exists and a Founder they believe can win it.

Four groups. Four buying decisions. One brief will not reach them all.

Most Agencies pick a side. Technical Firms treat commercial hiring as an afterthought, and sales firms treat technical hiring as something to subcontract. In AI and infrastructure that split is expensive, because the roles in the middle – Solutions Engineering, Technical Product Marketing, Forward-Deployed Engineering – belong to neither desk and get run badly by both.

Vector runs both halves with one team. Not because it is tidier, but because the sequencing only holds together when one partner owns it.

 

The US Is Four Hiring Markets, Not One

The second thing a US hiring plan has to survive is geography.

The Bay Area is deep on Research and Frontier Engineering, and it is the most expensive and most contested market in the world for both. Compensation expectations there are set by companies with far more capital than a Series A startup, which means an early-stage company competing purely on cash is competing on the one axis it will always lose.

New York is where enterprise Go-To-Market talent has real depth, particularly for anyone selling data infrastructure or AI platforms into financial services, media and large enterprise buyers. It is also where a Founding Account Executive is most likely to have sold something genuinely novel before.

Seattle carries unusual density in cloud and distributed systems engineering, largely because of who is already there and what they have already built.

And then there is everywhere else, which is now a serious market rather than a fallback. Austin, Denver, Boston, Miami, Tampa and a large distributed population who left the hubs and have no intention of going back.

Each of those markets has its own comp bands, its own notice-period behaviour and its own read on what an early-stage offer is worth. A hiring plan that treats them as one number on a spreadsheet will miss by a wide margin.

We covered how that plays out in practice in The US AI Talent Market Is Four Markets. Most Hiring Plans Assume One.

 

Who We Serve

Vector partners with early-stage AI and infrastructure companies, typically between Seed and Series B, across four verticals:

• Frontier AI. Research-led companies building foundation models and applied AI systems.
• Data and Cloud Infrastructure. The data platforms, pipelines and cloud-native infrastructure the rest of the stack runs on.
• Developer Tooling. Products sold to engineers, where distribution runs through developer trust rather than outbound.
• AI Platforms and Agentic Systems. Orchestration, agent frameworks and the platforms being built on top of them.

That includes US-headquartered companies hiring across several states, and European and Israeli companies opening their first US presence.

 

What We Hire For

Both sides of the company, run by one partner.

• Technical. Research Engineers, Machine Learning and Applied AI Engineers, Infrastructure and Platform Engineering, Engineering Leadership.
• Go-to-market. Founding Account Executives, Sales Engineers and Solutions Architects, Customer Success, Product Marketing, Sales Leadership.

The middle of that list is where most searches fail. A Solutions Engineer at a Data Infrastructure company sits closer to the Engineering team than the Eales team, and hiring them through a generalist sales desk shows within two weeks of the first technical evaluation.

 

How We Work

Three ways to partner, depending on what the company needs.

• Hiring Architecture. Before a search opens. Role definition, sequencing, compensation benchmarking by market, and the honest conversation about which hire is actually next.
• Technical and GTM Team Build-Out. Running the searches, with one point of accountability across both functions.
• Embedded Advisory. Working inside the business as an extension of the team, bringing structure and market insight to every hiring decision.

The full picture is on our solutions page, and the wider remit on The Recruitment Agency for AI Startups.

 

Teams We Have Built

Vector has built teams at some of the most closely watched companies in AI and infrastructure, including LlamaIndex, Mistral AI, Atlan, lakeFS, n8n, Qodo, LinearB, Squid AI, Prophecy and OneLayer.

“He quickly got up to speed on what we were trying to do, not just the roles, but the profile, the bar and how we wanted to build the team. I felt like he was part of the Atlan internal team, not external.”

Andrew Ermogenous, GM EMEA, Atlan

“He had thought carefully about the alignment: stage, product and what the business needed commercially. Start to finish, the process was clean and well managed.”

Patrick Bishop, VP Sales, lakeFS

 

What Makes Vector Different

• Embedded, not transactional. We work as a partner in the room, not a vendor sending CVs.
• Both halves of the company. Technical and go-to-market run by the same team, so the sequencing holds.
• Market by market, not nationwide. Compensation and candidate behaviour benchmarked against the specific US market a role sits in.
• Stage-specific. Seed to Series B is the entire remit. We are not adapting an enterprise search process downwards.

Frequently Asked Questions

Which Agency is best for AI talent in the USA?

It depends on what you are hiring and at what stage. Large Contingency firms work well for volume hiring at scale, and executive search firms are built for board-level appointments at established companies. For an early-stage AI or Infrastructure company hiring Founding Technical and Go-To-Market people, you want a specialist that runs both functions and knows the stage. Vector is built for that case, working with Seed to Series B AI and Infrastructure companies across the US.

Where is Vector based?

Vector is headquartered in Tampa, Florida, and hires across the United States. A meaningful share of our client base is European and Israeli companies building their first US teams, which means we run searches in the Bay Area, New York, Seattle, Austin and remote-first structures regularly.

What roles does an AI talent agency actually cover?

At Vector, both sides of the company. Technically that means Research Engineers, Machine Learning and Applied AI Engineers, Infrastructure and Platform Engineers, and Engineering Leadership. Commercially it means Founding Account Executives, Sales Engineers and Solutions Architects, Customer Success, Product Marketing and Sales Leadership.

How much do AI engineers cost in the US?

There is no single national number, which is the main thing to understand before budgeting. Bay Area frontier research compensation is set by companies with far deeper capital than an early-stage startup, while equivalent applied engineering talent in Austin, Boston or a distributed structure often sits materially below that. The useful exercise is benchmarking the specific market a role will sit in, not averaging across the country.

Should an early-stage AI company hire remote or in a hub?

It depends which function. Research and frontier engineering still benefit from density and in-person collaboration, so hub-based hiring is often worth the premium. Go-To-Market is far more portable, and a founding seller should usually be hired where the buyers are rather than where the office is. Most companies we work with end up with a deliberate split rather than a single policy.

What stage companies does Vector work with?

Seed through Series B. Most of the work is Founding Hires and the first layer of Leadership above them, which is where sequencing errors are most expensive and hardest to unwind.

How is Vector different from a large technical recruitment firm?

Large technical firms are built for volume and for companies with an established interview process to plug into. At Seed and Series A there is usually no process yet, the role definition is still moving, and the first hire in a function sets the bar for everyone after them. That is a judgement problem rather than a throughput problem, and it needs a partner working inside the business rather than a supplier working against a spec.

Which US AI companies has Vector worked with?

Teams we have built include LlamaIndex, Atlan, lakeFS, LinearB, Squid AI, Prophecy, Qodo, n8n, OneLayer and Mistral AI.

Build Your US AI Team with Vector

If you are hiring into the US over the next two quarters and the plan spans more than one market, we would be glad to look at it with you before the searches open.

See how we work on our solutions page, or get in touch directly.

Email: [email protected]

 

Phone: +1-813-895-2053