We are hiring an AI and Automation Apprentice to train alongside experienced Microsoft consultants on real client work. You'll be building AI-powered applications and automating client operations across the Microsoft Azure & M365. Modern Microsoft AI tooling sits at the heart of how we deliver, from Copilot Studio to Microsoft Foundry.

Wage

£22,000 a year
Minimum wage rates (opens in new tab)
Opportunity to increase salary to £25,000 based on performance in the first 12 months.

Training course

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

Hours

Monday - Friday: 9.00am - 5.00pm.
37 hours 30 minutes a week

Start date

Monday 14 September 2026

Duration

1 year 6 months

Positions available

4

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

What you'll do at work

Please note that this is an apprenticeship position and therefore anyone with more than six months of professional experience working in AI and Automation, or who holds a degree or Master’s degree in a subject such as AI, will not be eligible. You will also need to commit to completing a Level 4 AI Automation Practitioner Apprenticeship.

Duties and responsibilities

You will spend time identifying use cases, designing, planning and building AI and Automation solutions for clients. You will work alongside the Chief Technology Officer, Principal Consultants and Lead Consultants to deliver and operationalise AI solutions using Microsoft technologies.

AI Solution Development, M365 Platform Design and Transformation:

• Build Power Apps, Power Automate flows, Power Pages and Copilot Studio agents that automate manual processes
• Integrate Copilot with Line-of-Business Systems such as Microsoft 365, SharePoint and Power Platform
• Run discovery and process-mapping sessions with client stakeholders to identify automation and AI candidates
• Produce Power BI dashboards and supporting data models that surface insight from operational data
• Help configure and govern Microsoft 365 Copilot deployments, including security, prompt design and adoption tracking
• Help design, prototype, and test AI solutions, including Large Language Model (LLM) integrations, retrieval-augmented generation, agentic workflows and structured-output patterns
• Build well-scoped components and ship them through GitHub and Azure DevOps pipelines
• Support evaluation, observability and prompt iteration for live AI features

Desired Skills

• Proven interest in AI, automation and modern software delivery using the Microsoft technology stack
• An interest in business, the world around you and how technology is changing
• An interest in using technology to solve business problems
• Strong interpersonal skills with the ability to work well both in a team and on your own
• A commitment to continuous learning and professional development
• A logical, structured approach to problem solving
• Attention to detail and ability to follow processes
• Self-motivation and integrity
• Experience using AI assistants such as Copilot, ChatGPT, Claude or Gemini in study, work or home

Where you'll work

2640 Kings Court
The Crescent Birmingham Business Park
Birmingham
West Midlands
B37 7YE

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

Training provider

DIGITAL NATIVE (UK) LIMITED

Training course

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

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