AI Engineer Apprentice

Hyperfinity Ltd

Leeds (LS1 2ND)

Closes in 26 days (Monday 10 August 2026)

Posted on 13 July 2026

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Summary

Launch your AI Engineer career as a Level 4 AI & Automation Practitioner Apprentice at Hyperfinity in Leeds City Centre. Hands-on projects, friendly mentors, and real impact from day one.

Wage

£24,000 a year

Minimum wage rates (opens in new tab)

Training course
Artificial intelligence (AI) and automation practitioner (level 4)
Hours
Days and shift to be confirmed.

37 hours 30 minutes a week

Start date

Monday 17 August 2026

Duration

1 year

Positions available

1

Work

Most of your apprenticeship is spent working. You’ll learn on the job by getting hands-on experience.

What you'll do at work

  • Build and test AI features
  • Develop internal AI tools
  • Experiment with prompts and models
  • Connect systems together
  • Test, document and improve

Where you'll work

St. Pauls House
23 Park Square South
Leeds
LS1 2ND

Training

Apprenticeships include time away from working for specialist training. You’ll study to gain professional knowledge and skills.

Training provider

QA LIMITED

Training course

Artificial intelligence (AI) and automation practitioner (level 4)

Understanding apprenticeship levels (opens in new tab)

What you'll learn

Course contents
  • Review, establish, follow and or amend policies and procedures on data and information security.
  • Follow ethical, responsible and safe working practices respecting confidentiality and sensitive organisational matters.
  • Undertake analysis to identify if automation is viable. Including assessing risks such as data quality, process maturity and unintended consequences of AI automation projects, such as the impact on job roles.
  • Engage with non-technical staff to understand their roles, responsibilities, and concerns when automation solutions are proposed and implemented. Adapt approach to support workforce needs when implementing solutions that impacts the workforce.
  • Support with the introduction, adaption, and implementation of change. Contribute to constructive dialogue between leaders and employees about the adoption of AI and automation solutions.
  • Review and complete workflow and process mapping to identify problems or inefficiencies and recommend solutions including pilots, incremental changes and scaling opportunities.
  • Use automation design tools to suit the organisational context to configure, adapt and implement AI or automation solutions, such as conversational agents, text processing AI, workflow automation platforms and cloud based SaaS or PaaS.
  • Create and refine prompts for AI tools, using iterative testing to achieve accurate and useful outputs.
  • Apply analytical and computational techniques using tools and datasets to design, evaluate, and optimise automation solutions.
  • Integrate AI and automation technologies to collect, process, and manage data effectively, enabling intelligent and efficient system operation.
  • Design, integrate, and test digital workflows and AI automation tools using APIs, connectors, or low-or no-code integration methods.
  • Iterate solutions based on testing and feedback to ensure reliability, security, accessibility, and alignment with organisational needs.
  • Identify opportunities to deliver automation. Support leaders in integrating ethical, empathetic approaches when decision-making.
  • Support in the identification and evaluation of opportunities for increased productivity. For example, use of low-or no-code tools, streamlining processes and use of AI platforms.
  • Make evidence based suggestions to support governance, outcomes and facilitate improvement for example cost benefit analysis.
  • Report on productivity and efficiency savings and the opportunities for automation and where applicable when automation does not improve experience or processes.
  • Contribute to sustainable and efficient AI and automation solutions.
  • Support with the delivery of training to technical and non-technical user groups or audiences adapting content and format responding to feedback and organisational context.
  • Contribute to the creation and or adaption of resources such as user guides, training materials, process documents to meet user requirements.
  • Work collaboratively to deploy AI and automation strategies. Support where required to deal with the impact of automation for example retraining, redeployment, or upskilling of affected staff.
  • Undertake data analysis, preparation, and conversion to support automation solutions.
  • Present and communicate information including the translation of technical concepts into accessible materials to support clear dialogue with stakeholders.
  • Work with others to achieve agreed outcomes or outputs. Provide evidence-based analysis and insight to leaders on the likely human impacts of automation projects.
  • Use project management principles, techniques and tools to support the development of clear, balanced communications and briefings, articulating both opportunities and risks.
  • Keep up to date with existing, evolving, emerging technologies and sector trends in AI, automation and technology including methods to evaluate vendor and supplier solutions.
  • Apply ethical and human-centred design principles when scoping, developing, and deploying automation and AI solutions, underpinned by robust governance.
  • Apply technical understanding to help align business needs with technical capabilities, supporting the development of solutions that are scalable, efficient, and aligned with the organisation’s strategic objectives.
  • Undertake assurance activities to evidence responsible AI and automation, including maintaining clear documentation of design and decision-making, contributing to risk assessments, and applying assurance frameworks to support compliance with organisational, regulatory, and ethical standards.
  • Apply algorithmic impact assessment and workforce equality monitoring techniques when scoping, implementing, and reviewing AI and automation projects. Gather and analyse relevant workforce data, identify potential equality risks, and contribute evidence-based recommendations to support fair and inclusive adoption.
  • Review, establish, follow and or amend policies and procedures on data and information security.
  • Follow ethical, responsible and safe working practices respecting confidentiality and sensitive organisational matters.
  • Undertake analysis to identify if automation is viable. Including assessing risks such as data quality, process maturity and unintended consequences of AI automation projects, such as the impact on job roles.
  • Engage with non-technical staff to understand their roles, responsibilities, and concerns when automation solutions are proposed and implemented. Adapt approach to support workforce needs when implementing solutions that impacts the workforce.
  • Support with the introduction, adaption, and implementation of change. Contribute to constructive dialogue between leaders and employees about the adoption of AI and automation solutions.
  • Review and complete workflow and process mapping to identify problems or inefficiencies and recommend solutions including pilots, incremental changes and scaling opportunities.
  • Use automation design tools to suit the organisational context to configure, adapt and implement AI or automation solutions, such as conversational agents, text processing AI, workflow automation platforms and cloud based SaaS or PaaS.
  • Create and refine prompts for AI tools, using iterative testing to achieve accurate and useful outputs.
  • Apply analytical and computational techniques using tools and datasets to design, evaluate, and optimise automation solutions.
  • Integrate AI and automation technologies to collect, process, and manage data effectively, enabling intelligent and efficient system operation.
  • Design, integrate, and test digital workflows and AI automation tools using APIs, connectors, or low-or no-code integration methods.
  • Iterate solutions based on testing and feedback to ensure reliability, security, accessibility, and alignment with organisational needs.
  • Identify opportunities to deliver automation. Support leaders in integrating ethical, empathetic approaches when decision-making.
  • Support in the identification and evaluation of opportunities for increased productivity. For example, use of low-or no-code tools, streamlining processes and use of AI platforms.
  • Make evidence based suggestions to support governance, outcomes and facilitate improvement for example cost benefit analysis.
  • Report on productivity and efficiency savings and the opportunities for automation and where applicable when automation does not improve experience or processes.
  • Contribute to sustainable and efficient AI and automation solutions.
  • Support with the delivery of training to technical and non-technical user groups or audiences adapting content and format responding to feedback and organisational context.
  • Contribute to the creation and or adaption of resources such as user guides, training materials, process documents to meet user requirements.
  • Work collaboratively to deploy AI and automation strategies. Support where required to deal with the impact of automation for example retraining, redeployment, or upskilling of affected staff.
  • Undertake data analysis, preparation, and conversion to support automation solutions.
  • Present and communicate information including the translation of technical concepts into accessible materials to support clear dialogue with stakeholders.
  • Work with others to achieve agreed outcomes or outputs. Provide evidence-based analysis and insight to leaders on the likely human impacts of automation projects.
  • Use project management principles, techniques and tools to support the development of clear, balanced communications and briefings, articulating both opportunities and risks.
  • Keep up to date with existing, evolving, emerging technologies and sector trends in AI, automation and technology including methods to evaluate vendor and supplier solutions.
  • Apply ethical and human-centred design principles when scoping, developing, and deploying automation and AI solutions, underpinned by robust governance.
  • Apply technical understanding to help align business needs with technical capabilities, supporting the development of solutions that are scalable, efficient, and aligned with the organisation’s strategic objectives.
  • Undertake assurance activities to evidence responsible AI and automation, including maintaining clear documentation of design and decision-making, contributing to risk assessments, and applying assurance frameworks to support compliance with organisational, regulatory, and ethical standards.
  • Apply algorithmic impact assessment and workforce equality monitoring techniques when scoping, implementing, and reviewing AI and automation projects. Gather and analyse relevant workforce data, identify potential equality risks, and contribute evidence-based recommendations to support fair and inclusive adoption.

Training schedule

The AI & Automation Specialist programme integrates live and online workshops with self-paced learning, employing a guided discovery approach for individual learner contexts.

Learners are assigned a Digital Learning Consultant (DLC) for personalised coaching and support. These specialists ensure their successful progress, wellbeing, and readiness for assessments.

Requirements

Share if you have other relevant qualifications and industry experience. The apprenticeship can be adjusted to reflect what you already know.

Skills

IT skills

Other requirements

Entry requirements:

  • Level 3 Qualification (Apprenticeship/A Levels/BTEC etc.) 
  • OR equivalent work experience (typically 2 years in a relevant role) 

AND

  • 5 x GCSE’s including English & Maths at Grade 4 (C) or above.

You may also have a combination of qualifications and experience which demonstrate the minimum foundation needed for the programme. In this instance you could still be considered for the programme.

If you hold international equivalents of the above qualifications, at the time of your application you must be able to provide an official document that states how your international qualifications compare to the UK qualifications. 

For more information please visit the UK ENIC website.

About this employer

Hyperfinity use data science and AI to help retailers make profitable pricing, marketing and retail media decisions. Put simply, they help retailers sell the right products, to the right people, for the right price. They employ a mix of tech and people to achieve great results for our clients. They work with a growing list of household names including; Morrisons, Costa Coffee, Hotel Chocolat, Card Factory, Toolstation, Beaverbrooks. TG Jones, Subway, Bensons for Beds and JD Sports.

Company benefits

A range of exciting benefits are available!

After this apprenticeship

Your earnings can increase over time with an apprenticeship. Find out about potential future pay (opens in new tab).

Supporting Hyperfinity as an AI Engineer.

Ask a question

The contact for this apprenticeship is:

QA LIMITED

The reference code for this apprenticeship is VAC2000042076.

Apply now

Closes in 26 days (Monday 10 August 2026)

After signing in, you’ll apply for this apprenticeship on the company's website.