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Consortia
Consortia

Engineering

AI Engineer Recruitment

Specialist AI engineer recruiters working across the US, UK, EU and UAE.

Trusted by tech teams from start-ups to globally recognised brands

  • eBay
  • Ocado
  • Sainsbury's
  • Bose
  • LexisNexis
  • Entain
  • babylon
  • Paymentsense
  • FNZ
  • Auto1
  • Synthace
  • PokerStars
  • eConsult
  • Lloyds Pharmacy
Five-star review
“Every candidate they sourced was an exact match, which saved us real time. More of a trusted partner now than a recruiter.”

Mark T. · Director of Engineering, HR-tech platform

5.0 on Google from 200+ reviews

Overview

Companies hiring AI engineers usually want the same thing: someone who can take a model from a promising demo to something that works in front of real users. Consortia recruits AI engineers for SaaS, data and platform businesses on permanent and contract terms across the UK, Europe, the US and the UAE.

The title covers a wide range of work. Most AI engineering hires are applied software engineering: connecting large language models to a product through APIs, retrieval and evaluation, then making the result fast and reliable enough to ship. Where the work is closer to training and serving models, the hire is usually a machine learning engineer. We agree which version of the role you need before we search, then assess candidates on that basis rather than on a list of AI keywords.

How we recruit AI engineers

Many roles we recruit are founding or early hires, building a product with a small team. We are direct about what that means: funding, runway, equity, long hours and often five days in the office. Some candidates decide on the first call it is not for them, which saves everyone time.

For early roles, we often ask candidates to describe, in writing and in their own words, a project they took from idea to production. It shows how they think about data, trade-offs and ownership. It also gives founders something more useful than a CV.

We want to hear about production work: what they built, how they handled cost and reliability, and how they use AI tools day to day. Engineers from large tech companies can do well here. We check they are ready for the pace of a small team.

Some early-stage clients have no fixed band and trade base salary against equity. We take candidates' expectations for base and total pay separately, so both sides can see where an offer could land.

Market insights· Updated September 2026

AI Engineer recruitment insights

AI engineer is one of the fastest-growing job titles in UK tech, and experienced people are in demand.

The adverts show what the job has become. Most ask for Python and experience with Microsoft's cloud AI tools, and only a minority mention machine learning. In practice, most AI engineers build products on top of existing AI models rather than creating new ones. Many work in larger organisations, not just start-ups.

The pay premium is strongest for experienced people. Plenty of candidates now list AI on their CV. Far fewer have launched an AI feature and kept it working reliably, at a sensible cost, once real customers are using it.

A brief that explains what the AI will do, what data it relies on and who looks after it once it is live tends to attract people who have done this before.

Customer Stories

How we've helped

Salary guide

AI Engineers salaries

These ranges reflect what employers are advertising right now. Accepted offers can look different. Speak to a consultant about what's actually getting accepted.

We track what UK employers are advertising for this role. Ask us for the current ranges.

Work email only, we send guides to hiring teams.

FAQs

Frequently asked questions

What is the difference between an AI engineer and a machine learning engineer?

An AI engineer usually builds products on top of existing models, connecting them through APIs, retrieval and evaluation, then making the result fast and reliable. A machine learning engineer works closer to the models themselves, training, tuning and serving them. Many briefs use the titles loosely, so we agree which kind of work the role involves before we search.

How can you tell prototype experience from production experience?

We ask what happened after the demo. Candidates with production experience can talk about cost, latency and accuracy once real users arrived, how they evaluated output, and what they did when the model got things wrong. Plenty of people have built impressive prototypes. Fewer have kept an AI system working well at scale.

Could we train our existing software engineers instead of hiring?

Often, yes, for applied work built on existing models. Strong software engineers can pick up much of it. What tends to help is one engineer who has already shipped AI features in production, setting up evaluation, guardrails and good habits for the rest of the team. That can be quicker and safer than everyone learning from scratch.

Does an AI engineer need a research background or a PhD?

For most applied AI engineering roles, no. Strong software engineering, product sense and experience with evaluation matter more. Research depth becomes more relevant when the work involves training or adapting models, which is usually a machine learning or research role. Asking for a PhD where it is not needed narrows the pool a great deal.

How do I start working with Consortia?

Clients can get in touch to discuss a brief, and candidates are welcome to register their interest. The quickest route is our contact page or a call to +44 203 397 4565, and one of our consultants will pick things up from there.

For clients

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For candidates

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Browse live tech roles or send us your CV. A specialist consultant reviews every submission.

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