AI Engineer Jobs

Developers who build and deploy AI systems, from research to production. A role that bridges the gap between theory and application, with a focus on creating intelligent software solutions.

Open roles
184
Salary range
£28k – £300k
Hiring companies
63

AI Engineers are at the forefront of technological innovation, designing and implementing AI systems that solve complex problems. They work across a range of industries, from tech giants to research-heavy startups, and their role involves both theoretical research and practical application. AI Engineers are responsible for developing algorithms, models, and systems that can learn from data, make predictions, and automate tasks. This role requires a strong foundation in computer science, mathematics, and statistics, as well as proficiency in programming languages like Python and frameworks like TensorFlow and PyTorch.

What the role does

Inside the role of an AI Engineer

A typical week for an AI Engineer is a mix of research, development, and collaboration. They spend time coding, testing, and refining models, while also engaging with cross-functional teams to integrate AI solutions into existing systems.

  1. 01
    Design and implement machine learning models
  2. 02
    Optimise algorithms for performance and efficiency
  3. 03
    Collaborate with data scientists and software engineers
  4. 04
    Conduct experiments and analyse results
  5. 05
    Document processes and findings
  6. 06
    Stay updated with the latest AI research and tools
Salary on the board

£28k – £300k

Based on advertised midpoints across the 317 priced listings posted in the last 12 months. Base salary only.

By seniority
£k base
Entry
35
55
2 jobs
Junior
45
95
1 job
Mid
28
130
51 jobs
Senior
40
300
44 jobs
Lead
60
150
13 jobs
Director
120
209
4 jobs
Skills & tools

What hiring managers ask for

% of 149 listings posted in the last 12 months that mention each skill, extracted from job descriptions.

Python
76%
RAG
33%
AWS
32%
Azure
32%
CI/CD
29%
Machine Learning
26%
LangChain
26%
Prompt Engineering
25%
LLMs
22%
AI
21%
Generative AI
20%
Kubernetes
19%
Career ladder

From Junior to Principal

A typical UK progression for ai engineers. Years are guidance — strong people move faster, and many senior folks sidestep into research, product or management.

  1. Level 1

    Junior AI Engineer

    0–2 yrs

    Assist in the development and testing of AI models, with a focus on learning and gaining hands-on experience.

  2. Level 2

    AI Engineer

    2–5 yrs

    Take ownership of specific projects, from initial design to deployment, and contribute to the overall architecture of AI systems.

  3. Level 3

    Senior AI Engineer

    5–8 yrs

    Lead the development of complex AI solutions, mentor junior team members, and ensure the quality and reliability of AI systems.

  4. Level 4

    Principal AI Engineer

    8+ yrs

    Drive strategic initiatives, innovate in AI research, and guide the technical direction of the organisation.

Pathway

How to become a AI Engineer

There's no single route, but most people follow some version of these steps.

  1. 1

    Learn the Fundamentals

    Gain a strong foundation in computer science, mathematics, and statistics. Familiarise yourself with programming languages like Python and AI frameworks.

  2. 2

    Build Practical Skills

    Work on personal or open-source projects to apply your knowledge. Participate in hackathons and coding challenges to gain real-world experience.

  3. 3

    Gain Industry Experience

    Start your career as a Junior AI Engineer, working on smaller projects and learning from more experienced colleagues.

  4. 4

    Specialise in a Domain

    Choose a specific area of AI, such as computer vision or natural language processing, and deepen your expertise in that domain.

  5. 5

    Lead Projects

    Take on more responsibility by leading AI projects, managing teams, and ensuring the successful delivery of AI solutions.

  6. 6

    Innovate and Influence

    Contribute to cutting-edge research, influence the direction of AI in your organisation, and mentor the next generation of AI Engineers.

Live jobs

184 live roles

See all 184 roles
Spotlight
Bodyswaps logo

Senior AI Engineer

This role involves leading a two-year R&D project to develop emotionally responsive virtual humans for soft-skills training. Responsibilities include setting technical direction, building AI systems that perceive and respond naturally, and collaborating across multiple disciplines to turn research into a reliable product.

Bodyswaps London, United Kingdom
Hybrid Permanent
Clovo logo

AI Engineer

This role involves developing and deploying AI-powered features in a regulated healthcare environment, focusing on translating clinical and product requirements into secure, production-ready systems. The engineer will work across the full development lifecycle, integrating large language models and machine learning components into backend services while ensuring safety, reliability, and compliance. Collaboration with clinical and product teams is central to building measurable, patient-facing AI solutions.

Clovo Glasgow, United Kingdom £38,000 – £56,000 pa
On-site Permanent
Luminance logo

AI Engineer

This is a fantastic opportunity to join Luminance, the pioneer of Legal-Grade™ AI for enterprise. Backed by internationally renowned VCs and named in both the Forbes AI 50 list of ‘Most Promising Private AI Companies in the World’ and Inc....

Luminance Cambridge, United Kingdom
Hybrid Permanent

AI Engineer

This role involves developing and deploying AI applications, analyzing model performance, and working with multicore techniques. You will be part of a team focused on AI acceleration, using frameworks like PyTorch and TensorFlow, and tackling complex problems in AI model deployment and optimization.

MicroTech Consulting Barcelona, PL13 2JU, United Kingdom €68,698 – €69,568 pa
On-site Permanent

AI Engineer

This role involves designing and building production-ready AI features using large language models, machine learning, and retrieval-augmented generation (RAG) to enhance digital products. The engineer will bridge AI concepts with real-world applications, focusing on automation, product intelligence, and responsible AI practices. Collaboration with product teams and engineers is key to delivering secure, scalable solutions grounded in business needs.

Crowd Digital Ltd Bradford, West Yorkshire, United Kingdom £60,000 – £70,000 pa
Hybrid Permanent

AI Engineer

The AI Engineer will design and deploy scalable AI and machine learning systems, focusing on productionizing LLMs and GenAI solutions. Key responsibilities include building RAG pipelines, optimising model performance, implementing MLOps/LLMOps workflows, and ensuring responsible AI practices. The role involves close collaboration with data scientists and architects to deliver secure, real-time AI capabilities within complex digital transformation initiatives.

Vallum Associates London, United Kingdom £430 – £500 pd
Hybrid Contract

AI Engineer

You will design and implement AI and machine learning solutions using Python, integrating cutting-edge technologies into new products. The role involves mentoring junior developers and working within a collaborative engineering team focused on innovation. You will work with tools like TensorFlow, PyTorch, and GenAI frameworks, contributing to impactful service enhancements.

Cathcart Technology Edinburgh, Alba / Scotland, United Kingdom £500 – £600 pd
Hybrid Contract

AI Engineer

Design and deploy production AI systems using LLMs across customer support, safer gambling, compliance, and personalisation. Build agent workflows, RAG pipelines, and retrieval systems with a focus on safety, observability, and regulatory compliance in a high-traffic, real-time environment.

Parkside London, United Kingdom £50,000 – £90,000 pa
Hybrid Permanent
FAQs

Common questions

  • Python is the most widely used language in AI, but knowledge of C++, Java, and R can also be beneficial.

  • Strong programming skills, a solid understanding of algorithms and data structures, and proficiency in machine learning frameworks are crucial.

  • While a PhD can be beneficial, especially for research roles, many successful AI Engineers have backgrounds in computer science or related fields without a PhD.

  • Salaries for AI Engineers can vary widely based on experience, location, and industry. For more detailed salary information, please refer to the salary section on this page.

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