Artificial Intelligence Consultant

Peaple Talent
City of London
1 month ago
Applications closed

Related Jobs

View all jobs

Artificial Intelligence (AI) Consultant

Artificial Intelligence (AI) Consultant

Experienced Recruitment Consultant – Artificial Intelligence

Experienced Recruitment Consultant – Artificial Intelligence & Bio Artificial Intelligence Manchester (Hybrid)

Data Science Trainee

Data Science Trainee

Job Description

AI Partner | London (Hybrid) | £80,000 - £95,000


We’re working with a digital delivery business that connects organisations with high-quality near- and offshore development teams. As AI becomes core to modern software delivery, they’re hiring an AI Partner with a strong software engineering background to shape how AI capability is assessed, embedded, and scaled across their partner network.


This role is for a hands-on engineer, not a theorist, who can evaluate real-world AI systems, review code and architectures, and build internal tools that improve how partners are vetted and matched to client work.


What You’ll Do

  • Identify and onboard AI-capable development agencies with proven engineering depth
  • Technically vet partners through code reviews, architecture discussions, and solution assessments
  • Own and evolve an AI maturity model grounded in real software delivery experience
  • Act as a technical authority for sales and delivery teams on AI-led projects
  • Build internal AI automations and tooling using APIs, scripts, or no/low-code platforms


What We’re Looking For

  • Extensive experience as a software engineer (backend or full-stack preferred)
  • Proven hands-on experience with AI tools (e.g....

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.