AI Practitioner Apprentice

EXLSERVICE (UK) LIMITED

London (EC3N 1DD)

Closes in 28 days (Friday 10 April 2026 at 11:59pm)

Posted on 12 March 2026

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Contents

Summary

As a Junior AI Consultant Apprentice, you will support the design, architecture, and implementation of agentic AI solutions and AI-enabled enterprise.

You will work alongside senior AI architects and consultants to help shape next‑generation AI systems.

Wage

£29,000 a year

Check minimum wage rates (opens in new tab)

Wage - £29k - £30kp/a

Training course
Artificial intelligence (AI) and automation practitioner (level 4)
Hours
Monday - Friday (9:00am - 5:30pm). Shifts TBC.

37 hours 30 minutes a week

Start date

Tuesday 14 April 2026

Duration

1 year 6 months

Positions available

3

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

As a Junior AI Consultant Apprentice at EXL, you will support the design, architecture, and implementation of agentic AI solutions and AI-enabled enterprise.

You will work alongside senior AI architects and consultants to help shape next‑generation AI systems that combine GenAI, agentic automation, data intelligence, and enterprise application integration.

This role is designed for individuals who want to become AI architects or AI consultants, not data engineers.

Key Responsibilities

AI-enabled systems & agentic AI support

You will:

  • Support design and prototyping of agentic AI applications embedded into client workflows
  • Assist in building tool-enabled AI agents, orchestrating APIs, knowledge sources, and enterprise systems
  • Participate in evaluating AI system behaviour (accuracy, drift, reliability, safety)
  • Help configure enterprise AI applications using EXL’s toolkits and accelerators

AI systems architecture & workflow integration

You will support senior architects to:

  • Map current client processes and identify opportunities for embedded AI
  • Design end-to-end AI architectures including memory models, orchestration layers, vector stores, and workflow integration patterns
  • Assist in documenting solution architectures, data flows, and integration designs
  • Help prepare architectural artefacts for client presentations (diagrams, solution blueprints, implementation plans)

Industry-focused AI consulting

You will work on AI use cases across:

  • Insurance – underwriting support, claims automation, broker-assist, fraud
  • Banking – KYC/AML workflow AI, credit operations, customer servicing
  • Energy & Utilities – field operations, network planning, customer queries
  • Retail – demand forecasting, merchandising, customer support workflows
  • Your contribution will focus on translating industry problems into AI-enabled solutions

Sales enablement & pre-sales support

You will:

  • Support proposal creation, case studies, POVs, AI maturity assessments
  • Help prepare demos for client meetings, including AI agent workflows
  • Assist senior team members in producing slide decks & architectural narratives
  • Contribute to benchmarking, competitive analysis, and value case modelling

Responsible AI & Governance

You will:

  • Apply principles of safe AI, EU AI Act and FCA-aligned controls
  • Support testing and evaluation frameworks (TEVV) including:

- Accuracy, precision/recall

- Groundedness

- Consistency

- Safety checks

Help maintain audit trails, evaluation logs, and architecture documentation

Essential Knowledge

You must have foundational knowledge or experience in:

  • Understanding of AI concepts: LLMs, RAG, agentic workflows, vector databases
  • Basics of enterprise workflows and integration patterns
  • Fundamentals of cloud platforms (Azure, AWS, GCP) and modern application architectures
  • Familiarity with Python or TypeScript for prototyping
  • Basic understanding of data models and APIs

Essential Skills

  • Strong analytical and problem-structuring ability
  • Ability to break down business processes and map AI opportunities
  • Clear communicator capable of producing client-ready materials
  • Interest in architecture (logical diagrams, solution blueprints, systems thinking)
  • Ability to collaborate across business, IT, and data teams 

Where you'll work

Saint Clare House, 30 33 Minories,
London
EC3N 1DD

Training

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

Training provider

JUST IT TRAINING 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 solutions for example Zapier, Make and Power Automate.
  • 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 solutions for example Zapier, Make and Power Automate.
  • 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

An apprenticeship includes regular training with a college or other training organisation.

At least 20% of your working hours will be spent training or studying
Artificial intelligence (AI) and Automation Practitioner standard Level 4

You will also receive full training and support from the Leep Talent Apprenticeship team to increase your skills.

Your training will include gaining a Level 4 Artificial intelligence (AI) and Automation Practitioner qualification.

Learners can gain these optional exams at the end of the programme:

  • AWS Certified AI Practitioner
  • Microsoft AI-900 Azure AI Fundamentals
  • Microsoft PL-900 Fundamentals
  • Awarding Body: Accelerate People

Requirements

Essential qualifications

GCSE in:

  • English (grade 4/C +)
  • Maths (grade 4/C +)

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
  • Problem solving skills
  • Presentation skills
  • Administrative skills
  • Number skills
  • Analytical skills
  • Logical
  • Team working
  • Creative
  • Initiative
  • Interest in AI
  • Motivated
  • Can do attitude
  • Interest in architecture
  • Tech Savvy

About this employer

From our beginnings in business process services to becoming a global leader in data and AI, EXL brings 25+ years of proven expertise helping enterprises transform and redefining what's possible for our clients.

We partner with leading companies in insurance, healthcare, banking and capital markets, retail, media and communications, and energy and infrastructure to reimagine business models, deliver measurable outcomes, and accelerate innovation.

While nearly 70% of enterprise AI initiatives fail, EXL consistently delivers a 90% success rate by integrating deep industry knowledge, robust data and analytics capabilities, and cutting-edge AI implementation in client workflows—turning complexity into value at scale.

At EXL, innovation isn't just a buzzword—it's how we solve complex challenges and create lasting value. By integrating cutting-edge technologies like machine learning, AI, and cloud computing, we enable our clients to stay ahead of the curve. Whether it's revolutionizing customer experiences, streamlining back-office operations, or uncovering new revenue streams, innovation fuels everything we do.

After this apprenticeship

Over 90% of our apprentices move on to permanent full-time employment in the tech industry. There are also opportunities to extend your training with a higher-level Apprenticeship Programme.

We have already helped over 1000 people start their tech and digital careers with an apprenticeship.

Ask a question

The contact for this apprenticeship is:

JUST IT TRAINING LIMITED

nina.fosu@leepgroup.com

The reference code for this apprenticeship is VAC2000020914.

Apply now

Closes in 28 days (Friday 10 April 2026 at 11:59pm)