AI Engineer

Pret A Manger

Manchester

On-site

GBP 70,000 - 110,000

Full time

6 days ago

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Job summary

Pret A Manger is seeking an AI Engineer to design, build and operate practical AI agents, automations and orchestration across Copilot Studio, Azure AI Foundry and Power Platform to boost productivity and customer experience.

You will own end-to-end delivery from architecture to handover, collaborating with Support Centre functions, shops, markets and tech teams, while delivering production-ready AI solutions and ensuring security, scalability and governance.

Qualifications

2–6 years in applied AI, software or automation engineering with production examples.
Active interest in AI and automation; building agents/workflows or infra-adjacent tools.
Infrastructure, platform or cloud engineering background is a strong plus.
Demonstrable architecture-level judgement to make platform decisions unsupervised.
Hands-on Microsoft Copilot Studio with orchestration and debugging.
Power Automate and Power Platform experience, including Dataverse modelling.
Python development with testing, version control and CI/CD.
Hands-on Azure, Function Apps and cloud-native deployment.
Practical production experience with LLMs, including prompt orchestration and RAG.
Ability to reason Copilot-vs-Foundry decisions and explain trade-offs.
Excellent written communication and structured fault-finding.
Nice-to-have: Azure AI Foundry, Azure AI Search, Semantic Kernel, AB-620/AI-102/103.

Responsibilities

Discovery and PoC: identify high-value automation opportunities with business BA inputs.
Prototype and test proofs of concept quickly, testing feasibility and value.
Decide platform calls for opportunities with justified reasoning.
Take ideas to production with end-to-end ownership and governance.

Skills

Applied AI

Software engineering

Automation engineering

Copilot Studio

Power Automate

Python

Azure

LLMs in production

Architectural judgement

Documentation

Communication skills

Security and governance

Tools

Azure Functions

Azure Foundry

Dataverse

Power Platform

REST APIs

CI/CD pipelines

Job description

We’re Pret: proud makers of freshly made food, organic coffee, and big ideas. Across 750+ shops and 20+ countries, our teams are shaping the future of Pret through innovation, inclusion, great customer service and a shared passion for doing the right thing. We’re growing fast on our mission to be the employer of choice in hospitality, everywhere we operate – so this an exciting time to hop on board.

We Believe in Growing Good Things

Growth is at the heart of everything we do. From the freshly hand‑made food we create every day, to supporting our teams, we help our people grow in confidence, skills and to pursue their unique paths. Pret is where passionate, hardworking, wonderful people (like you!) find what they need to shine. And the proof is in the pudding – over 80% of our Managers started on the shop floor! So did 20% of our Support Centre teams, including our CEO, Pano.

What we’re looking for

We’re looking for passionate team players to bring joy to our customers every day. As a AI Engineer you’ll play a central role in building how work gets done across Pret’s global functions. This is not a traditional software engineering role. The focus is to design, build and operate practical AI agents, automations & orchestration across Copilot Studio, Azure AI Foundry & Claude that improve productivity, decision‑making, customer experience and team effectiveness.

This is a sole‑builder role: you will own delivery end‑to‑end, from architecture and platform choice through to build, testing and handover, rather than leading a team from day one. You will work across Support Centre functions, shops, markets, technology teams and third‑party suppliers to turn business opportunities into working solutions, moving them from proof of concept through to production using Copilot Studio, Azure AI Foundry, Power Platform and Azure.

The role combines strong engineering fundamentals with AI fluency, automation and solution design. You will build agents across knowledge, actions and instructions, exercising clear judgement on which platform a use case belongs on, ensuring solutions are useful, safe, scalable and adopted by the teams they support. You will be mentored technically by the Automation Manager but are expected to work independently as the hands‑on architect and builder for the AI agent estate, with real ownership over the calls that will shape it long after the team has grown.

Key responsibilities

Discovery and proof of concept: most of your time in the first phase

Work directly with the business and Business Analysts to identify high‑value automation and AI opportunities that fundamentally re‑design what we do today
Scope and build working proofs of concept fast, testing feasibility and likely value before committing to a production build.
Make and defend the platform call (Copilot Studio vs Foundry vs. Claude) for each opportunity, with the reasoning to back it up.
Support the appropriate documentation and knowledge repositories as we lay the foundations for required governance and controls

Taking proven ideas to production

Take POCs that demonstrate real business value from prototype through to a production‑grade agent or automation inc. all required testing & validation
Build Copilot Studio agents (conversation flows, fallback strategies, Adaptive Cards in Teams) where the use case calls for low‑code.
Build pro‑code Foundry agents using Python, Azure Functions, custom skills and workflows where the use case calls for it.
Develop Power Automate cloud flows with real orchestration: error handling, retries, long‑running operations.
Model and integrate data, connectors, REST APIs and MCP servers, with security and auditability built in from the start.

Platform, architecture and governance: ongoing, and what the 2027 team inherits

Own the end‑to‑end architecture of the AI agent estate: you make the platform and design calls, and escalates trade‑offs to the Automation Manager.
Choose the right knowledge and retrieval strategy (managed RAG, owned RAG or live query) for each use case.
Build eval sets, retrieval‑quality checks, guardrails and observability, and deploy via CI/CD.
Work within the environment strategy and DLP policies; ensure retrieval is permission‑aware by design.
Document every agent and every promotion decision to a genuinely handover‑ready standard. This is the foundation the 2027 team builds on, not paperwork for its own sense.
Ensure we build agents in a cost‑effective way to maximise the ROI and ensure we deliver within budget

Experience and Skills required

2–6 years in applied AI, software or automation engineering, with a portfolio or real production examples.
A genuine, active interest in AI and automation: you’re already building agents, workflows or infra‑adjacent tools in your own time, not just at work.
Infrastructure, platform or cloud engineering background is a strong plus: comfort with production operations, monitoring and reliability, not just prototyping.
Demonstrable architecture‑level judgement: able to make and defend platform and design decisions unsupervised, as this role has no engineering peer group to lean on day‑to‑day.
Hands‑on Microsoft Copilot Studio, including topic authoring, generative orchestration, connectors, knowledge sources and debugging.
Power Automate and the wider Power Platform, including Dataverse data modelling and security roles.
Python development with sound engineering habits (testing, version control, CI/CD).
Hands‑on Azure, ideally Function Apps, and cloud‑native deployment.
Practical experience of LLMs in production, including prompt orchestration, RAG and output evaluation.
Ability to reason about Copilot‑vs‑Foundry and knowledge‑design decisions and explain the trade‑offs.
Excellent written communication and structured fault‑finding. This role must document to a standard that lets someone else pick up the work.
Advantageous: Azure AI Foundry (Agent Service, Prompt Flow), Azure AI Search, Semantic Kernel or the Microsoft Agent Framework, machine learning/forecasting and certifications AB‑620 and AI‑102/103.