AI Practitioner Level 4 Apprenticeship
VIVID CARE SERVICES LIMITED
Manchester (M17 1LB)
Closes in 18 days (Saturday 20 June 2026 at 11:59pm)
Posted on 2 June 2026
Contents
Summary
Seeking a confident individual with good communication skill, able to work independently, enjoy task with excitement when achieve a good outcome. Someone who is active, needs to be occupied, willing to think out of the box, who is not afraid to face challenging situations, who can work under pressure and focus on the vision of the business.
- Wage
-
£16,640 for your first year, then could increase depending on your age
National Minimum Wage rate for apprentices
- Training course
- Artificial intelligence (AI) and automation practitioner (level 4)
- Hours
-
Monday - Friday, 9.00am - 5.00pm
40 hours a week
- Start date
-
Wednesday 1 July 2026
- Duration
-
1 year 8 months
- 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
- Blended learning, including interactive workshops, monthly 1:1 sessions, personalised coaching and tutor support
- The programme is designed to help learners build the skills to solve real business problems and create AI-powered solutions
- Apprentices will develop knowledge of AI concepts, tools, platforms, data analysis, model building, automation, prompt engineering and responsible AI practice
Where you'll work
Warren Bruce Court
Manchester
M17 1LB
Training
Apprenticeships include time away from working for specialist training. You’ll study to gain professional knowledge and skills.
Training provider
MBKB LTD
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
Artificial Intelligence (AI) and Automation Practitioner Level 4.
Course content includes:
- Introduction to AI and Machine Learning
- Data Collection, Preparation and Analysis
- AI Model Building and Evaluation
- Prompt Engineering and Generative AI
- Responsible AI, Ethics and Bias
- AI Tools, Platforms and Automation
- Visualising Data and Communicating Insights
- Real World AI Projects and Problem Solving
Learners will also gain skills in:
- Understanding AI concepts, technologies and applications
- Collecting, preparing and analysing data responsibly
- Building, testing and evaluating AI models and solutions
- Working with AI tools, platforms and programming languages
- Applying AI ethically in line with governance and regulations
- Communicating insights and creating value through AI solutions
- Continuously improving AI systems and ways of working
Support included:
- Live online workshops via Microsoft Teams
- Monthly 1:1 coaching and progress reviews
- Dedicated tutor and apprentice support
- Flexible learning alongside the learner’s day to day role
- Access to resources, tools and career development support
End Point Assessment:
At the end of the apprenticeship, learners complete an End Point Assessment to confirm occupational competence. This includes a work based project where they apply their knowledge and skills to a real business challenge within their organisation. There are also one additional EPA activity chosen by the learner and employer from the options provided by the assessment organisation
Candidate requirements:
This programme is best suited to candidates who already have previous project management experience and are now looking to change career or move into the AI space. The ideal learner should be comfortable managing projects, working with stakeholders, solving business problems and applying structured thinking to real workplace challenges.
They do not need to already be an AI expert, but they should have a strong interest in AI, data, automation and digital transformation, with the ambition to develop practical AI skills that can be applied within a care sector environment.
The apprenticeship would be a strong fit for someone looking to use their existing project management background as a foundation to progress into AI-focused roles, AI implementation, digital transformation, automation or AI project delivery.
Requirements
Essential qualifications
GCSE in:
Share if you have other relevant qualifications and industry experience. The apprenticeship can be adjusted to reflect what you already know.
Skills
- Communication skills
- IT skills
- Attention to detail
- Organisation skills
- Customer care skills
- Presentation skills
- Administrative skills
- Logical
- Team working
- Creative
- Initiative
- Patience
About this employer
We are a care provision with supported living and agency and training company
After this apprenticeship
Full career progression available.
Ask a question
The contact for this apprenticeship is:
MBKB LTD
Nicki Bevan
recruit@mbkbgroup.com
The reference code for this apprenticeship is VAC2000034564.
Apply now
Closes in 18 days (Saturday 20 June 2026 at 11:59pm)