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
154
Salary range
£28k – £300k
Hiring companies
51

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

154 live roles

See all 154 roles

Product Design Engineer - AI-Native Products - Morgan McKinley

This role involves designing and building AI-native product experiences for internal employee-facing platforms, creating new interaction patterns for conversational and AI-assisted workflows, and defining design systems for AI-powered products. You will work closely with Product Managers, Engineers, and AI specialists to shape product direction and continuously improve user experiences through user research and usability testing.

eFinancialCareers London, United Kingdom
Remote Permanent Flexible
NVIDIA logo

Senior Networking Solution Test Engineer – AI Cluster Debugging

As a Senior Networking Test Engineer, you will design and maintain test environments for large-scale AI clusters, focusing on NVLink, Ethernet, and InfiniBand technologies. Your role involves deep debugging of hardware, system software, and AI workloads, collaborating with development teams to resolve complex issues and optimize performance.

Remote Permanent

Director, Engineering Excellence AI Platforms - Citi

This role involves leading the development and delivery of high-impact engineering platforms with a focus on Generative AI and modern engineering practices. You will build and develop a high-performing engineering team, provide technical leadership, and collaborate with senior stakeholders to ensure solutions meet the needs of Citi's technology organization.

eFinancialCareers Belfast, United Kingdom
Hybrid Permanent
NVIDIA logo

Principal AI Developer Technology Engineer

We’re currently seeking a Principal Developer Technology Engineer, Artificial Intelligence. Would you enjoy researching parallel algorithms to accelerate AI workloads on advanced computer architectures? Do you find it rewarding to identify and eliminate system bottlenecks to achieve the best possible...

NVIDIA Bristol, United Kingdom

Software Engineer III - React / TypeScript, Gen AI, Frontend

As a Software Engineer III, you will design and develop secure, scalable frontend solutions with a focus on React, TypeScript, and AI-enabled user experiences. Your role involves building reusable UI components, optimizing performance, and collaborating with UX designers and product stakeholders to deliver high-quality, accessible interfaces.

JPMorgan Chase & Co. Central London, W3 0BJ, United Kingdom
On-site Permanent
Databricks logo

Pre-sales Senior Technical Solutions Engineer (Data and AI) x4

This role involves working closely with sales teams to demonstrate Databricks' Data Intelligence Platform to enterprise clients, focusing on data and AI solutions. You'll design technical proofs-of-concept, deliver custom demonstrations, and act as a trusted advisor on data architecture and AI use cases. The position requires deep technical expertise in big data, cloud ecosystems, and customer-facing pre-sales engineering, with regular engagement in client workshops and solution design.

Databricks London, United Kingdom
Hybrid Permanent
Databricks logo

Pre-sales Senior Technical Solutions Engineer (Data and AI)

Act as a technical advisor to customers during pre-sales engagements, demonstrating Databricks' Data Intelligence Platform through hands-on evaluations, custom demos, and solution architecture design. Collaborate with sales teams to translate customer data and AI challenges into effective technical solutions, while contributing to field communities through workshops and thought leadership.

Databricks London, United Kingdom
Hybrid Permanent

AI Enginnering Lead

Leads and develops an AI engineering team, shaping technical standards and delivering scalable AI solutions in production environments. Combines strategic leadership with hands-on technical work, including mentoring engineers and guiding AI architecture. Engages with clients and stakeholders to design and deploy modern AI systems using cloud platforms and agentic technologies.

Searchability Manchester, United Kingdom £100,000 – £125,000 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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