Artificial Intelligence Engineer

Formula Recruitment
City of London
1 day ago
Create job alert

AI Engineer

Location: Fully Remote

Salary: Up to $230,000


We have partnered with a fast-growing, product-led technology company building AI-powered systems to supercharge internal teams and deliver intelligent customer-facing solutions.


As the business scales, they’re hiring an AI Engineer to design and ship high-impact AI systems across internal tooling, developer experience, and production-grade customer applications.


What You’ll Do as an AI Engineer:

  • Design and ship AI-powered internal tooling that increases productivity across all teams.
  • Build AI-enhanced developer workflows, coding assistants, and automation systems.
  • Develop and maintain customer-facing AI support pipelines and production LLM systems.
  • Architect and scale Retrieval-Augmented Generation (RAG) systems for large knowledge bases.
  • Design and orchestrate agent and multi-agent architectures for complex task execution.
  • Integrate LLMs via providers such as OpenRouter, optimising for cost, latency, and performance.
  • Fine-tune domain-specific LLMs and continuously improve model performance.
  • Build and maintain workflow automation pipelines using tools like n8n and LangChain.
  • Implement LLM observability and monitoring across production systems.
  • Continuously evaluate emerging models, frameworks, and AI tooling to keep the company at the cutting edge.


What We’re Looking For in an AI Engineer:

  • Proven experience shipping AI systems into production environments.
  • Strong proficiency in Python and/or TypeScript/JavaScript.
  • Deep experience with LangChain, RAG systems at scale, and LLM fine-tuning.
  • Hands-on experience building agent or multi-agent architectures.
  • Experience with workflow automation tools such as n8n.
  • Strong understanding of model selection across providers and cost/performance trade-offs.
  • Familiarity with LLM observability tools (e.g. LangFuse, Weights & Biases).
  • Comfortable with basic DevOps and deploying AI systems reliably.
  • A product manager mindset — proactively identifying opportunities, understanding real user needs, and driving adoption of internal tooling.
  • Nice to Have's as an AI Engineer:
  • Experience with voice AI or multimodal systems.
  • Contributions to open-source AI projects.
  • Experience working with AI-native developer tools and modern AI IDE workflows.


This is a rare opportunity for an AI Engineer to architect and scale AI systems at the core of a company’s operations, directly influencing productivity, product capability, and long-term technical strategy.


**Unfortunately, due to high volume of applications, not all submissions will receive feedback.**

Related Jobs

View all jobs

Artificial Intelligence Engineer

Artificial Intelligence Engineer

Artificial Intelligence Engineer

Artificial Intelligence Engineer

Artificial Intelligence Engineer

Artificial Intelligence Engineer

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.