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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
152
Salary range
£28k – £300k
Hiring companies
51
View 152 live roles → Get an alert

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 297 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
48 jobs
Senior
40
300
38 jobs
Lead
60
150
10 jobs
Director
120
209
3 jobs
Skills & tools

What hiring managers ask for

% of 140 listings posted in the last 12 months that mention each skill, extracted from job descriptions.

Python
74%
AWS
34%
Azure
34%
AI
28%
LangChain
26%
Machine Learning
26%
CI/CD
25%
RAG
23%
LLMs
22%
Kubernetes
21%
Generative AI
20%
GCP
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

152 live roles

See all 152 roles →

AI Platform/ DevOps Engineer

This role involves designing, building, and operating cloud-native AI platform infrastructure across AWS and Databricks. Responsibilities include deploying and scaling containerised services, managing CI/CD pipelines, and implementing observability and security measures for AI workloads.

The Portfolio Group Ec4V4Dy, EC4V 4DY, United Kingdom £70,000 – £80,000 pa
On-site Permanent

Lead AI Engineer

This role involves designing and building scalable AI solutions using Generative AI, Agentic AI, and modern cloud platforms. You will lead technical delivery, mentor junior engineers, and contribute to engineering standards and best practices within a fast-paced, collaborative team environment.

eFinancialCareers London, United Kingdom £60,000 – £75,000 pa
Hybrid Permanent

Lead AI Engineer

Our client is building the most advanced AI platform in their market. They help their clients serve customers with unmatched speed and accuracy.They’ve invested heavily into building the ML stack, partnered with leading universities, and trained models on millions of...

Exposed Solutions Fitzrovia, W1T 5EE, United Kingdom
Remote

AI Forward Deployed Engineer

This role involves building and deploying production-grade AI applications that investment and finance teams rely on daily, while also contributing to the development of a governed AI platform. You will work closely with business teams to identify and solve real problems using LLM APIs and modern cloud infrastructure.

eFinancialCareers London, United Kingdom
Hybrid Contract

Senior AI Engineer Manager/Associate Director | Capital Markets

This role involves leading the design, build, and delivery of advanced AI solutions in financial services and capital markets. Responsibilities include building AI prototypes, working with LLMs, RAG patterns, and modern data platforms, and collaborating with multidisciplinary teams to solve complex challenges.

Datatech Manchester, United Kingdom
Hybrid Permanent

Senior AI Automation Engineer

This role involves designing, building, and deploying production-grade AI agents and automated workflows for internal business use within a regulated enterprise environment. The engineer will develop Python-based services, integrate AI systems with internal platforms using APIs and event-driven architectures, and ensure solutions are scalable, secure, and maintainable. The position emphasizes practical AI application over research, with a focus on real-world deployment and mentoring junior engineers.

Hays Technology London, City And County Of the City Of London, United Kingdom
Hybrid Permanent

Forward Deployed AI Engineer

This role involves working directly with end clients to deploy an AI and knowledge graph platform, leading technical delivery from scoping to production rollout. You will design and build AI-driven workflows, integrate knowledge graph data, and collaborate with both technical and non-technical stakeholders.

Harnham - Data and Analytics Recruitment London, United Kingdom £80,000 – £130,000 pa
Hybrid Permanent Flexible
NVIDIA logo

Senior HPC AI Cluster Engineer

This role involves designing, implementing, and maintaining large-scale HPC and AI clusters, working with the latest GPU and deep learning technologies. You will collaborate with researchers, developers, and customers to optimize system performance and develop new solutions.

NVIDIA Germany
Remote Permanent
See all 152 roles →
Top hirers

Companies hiring ai engineers

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Hiring locations

Where this role is hiring

The locations with the most live listings for this role today.

London

Location
46 open

Manchester

Location
7 open

Edinburgh

Location
3 open

Cambridge

Location
3 open

Birmingham

Location
2 open

Cardiff

Location
2 open
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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