National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

AI Engineer

Knightsbridge
2 weeks ago
Create job alert

I'm working with a global investment group that's scaling its Data & AI team — and they’re hiring a sharp AI Engineer to help build cutting-edge, business-ready AI solutions from the ground up.
This role is all about turning AI into action: you'll partner with domain experts to build bespoke LLM-powered apps (like internal Co-Pilots and RAG systems), drive adoption across teams, and embed models directly into business processes. Think real impact, not just proof of concept.

What You’ll Do:

Build and deploy AI products using Azure ML, LangChain, LangGraph, and Fabric tools
Lead Co-Pilot enablement across the firm and help shape data governance around AI use
Work closely with users to develop solutions that drive measurable results
Use your MLOps skills to monitor, scale, and refine models in productionWhat You’ll Bring:

5–8 years of applied AI/ML experience, ideally with LLMs and enterprise deployment
Hands-on experience with RAG systems, agentic workflows, and Azure ML tools
Confidence working with business users to design AI tools they’ll actually use
A pragmatic, value-first mindset and strong communication skillsWhy This Role?

Join a growing AI team with genuine buy-in from senior leadership
Own the full lifecycle of AI products — from design to adoption
Global exposure, modern stack, and the chance to shape a future-ready platform
You'll be working from their Knightsbridge office 4-5 days a week

Related Jobs

View all jobs

AI Engineer

AI Engineer

AI Engineer

AI Engineer

AI Engineer

AI Engineer - Generative AI - £60,000 - Remote

National AI Awards 2025

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 to Get a Better Machine Learning Job After a Lay-Off or Redundancy

Redundancy in machine learning can feel especially frustrating when your role was technically advanced, strategically important, or AI-facing. But the UK still has strong demand for machine learning professionals across fintech, healthtech, retail, cybersecurity, autonomous systems, and generative AI. Whether you're a research-oriented ML engineer, production-focused MLOps developer, or applied scientist, this guide is designed to help you bounce back from redundancy and find a better opportunity that suits your goals.

Machine Learning Jobs Salary Calculator 2025: Figure Out Your True Worth in Seconds

Why last year’s pay survey is useless for UK ML professionals today Ask a Machine Learning Engineer wrangling transformer checkpoints, an MLOps Lead firefighting drift alarms, or a Research Scientist training diffusion models at 3 a.m.: “Am I earning what I deserve?” The honest answer changes monthly. A single OpenAI model drop doubles GPU demand, healthcare regulators release fresh explainability guidance, & a fintech unicorn pays six figures for vector‑search expertise. Each shock nudges salary bands. Any PDF salary guide printed in 2024 now looks like an outdated Jupyter notebook—missing the gen‑AI tsunami, the surge in edge inference, & the UK’s new Responsible‑AI framework. To give ML professionals an accurate benchmark, MachineLearningJobs.co.uk distilled a transparent, three‑factor formula that estimates a realistic 2025 salary in under a minute. Feed in your discipline, UK region, & seniority; you’ll receive a defensible figure—no stale averages, no guesswork. This article unpacks the formula, highlights the forces driving ML pay skyward, & offers five practical moves to boost your value inside the next ninety days.

How to Present Machine Learning Solutions to Non-Technical Audiences: A Public Speaking Guide for Job Seekers

Machine learning is driving change across nearly every industry—from retail and finance to health and logistics. But while the technology continues to evolve rapidly, the ability to communicate it clearly has become just as important as building the models themselves. Whether you're applying for a junior ML engineer role, a research position, or a client-facing AI consultant job, UK employers increasingly expect candidates to explain complex machine learning solutions to non-technical audiences. In this guide, you’ll learn how to confidently present your work, structure your message, use simple visuals, and explain the real-world value of machine learning in a way that makes sense to people without a background in data science.