AI Engineer; AI Specialist

We’d all like amazing work to do, and real work-life balance. That’s waiting for you at Sainsbury’s. Think about the scale it takes to feed the nation. The level of data, transactions and variety involved. Then you’ll realise this is a modern software engineering environment, because it has to be. We’ve made significant investment in the standards and principles that shape how we work.

We iterate, learn, experiment and champion ways of working such as Agile, Scrum and XP. So you can look forward to exciting opportunities across everything from AI to reusable tech.

As a Staff AI Engineer, you will be the technical specialist connecting AI ambition to delivery reality across Sainsbury's Tech. This is a hands‑on engineering role with division‑wide scope. You will set the bar for how AI is engineered across the division, creating reusable patterns, defining standards and working across every Tech domain to ensure we build AI capabilities once and share them everywhere.

The role is intentionally cross‑cutting. Where most engineers go deep in one team, you will go wide across many, identifying duplication, reducing friction, and leaving every team you touch with stronger AI engineering capability than before.

This is not a policy role You'll write code, build proofs of concept, and solve hard problems alongside delivery teams. But your primary measure of success is the multiplier effect you create, not the features you ship directly.

• Define and champion reusable AI engineering patterns, accelerators, and reference architectures that delivery teams across Sainsbury's Tech can adopt with confidence.
• Translate proven engineering workflows into reusable skills and agents that standardise delivery, reduce duplication, and accelerate teams across Sainsbury's Tech.
• Work across Tech domains (Customer, Channels, Supply Chain and Logistics, Argos, Data and AI Ecosystem, and more) to identify duplicated effort, converge on shared approaches, and reduce the cost of building AI solutions.
• Lead technical discovery and feasibility assessment for high‑priority AI opportunities, providing clear, evidence‑based recommendations on viability, effort and expected value.
• Build and maintain a living library of production‑ready patterns covering areas such as RAG, agentic AI, LLM integration, prompt engineering and responsible AI guardrails.
• Facilitate cross‑domain engineering forums, design reviews, and communities of practice, creating the conditions for AI engineering knowledge to flow freely across the organisation.
• Work hands‑on alongside delivery teams to accelerate them through complex technical challenges, pairing, coaching, and transferring capability rather than taking over.
• Influence the AI and data platform roadmap, working with Platform Engineering, Architecture, and the AI Centre of Excellence to ensure strategic tooling meets the needs of delivery teams.
• Contribute to engineering standards and guardrails for AI development, ensuring solutions are secure, observable, responsible, and aligned to our strategic platforms.
• Stay ahead of the rapidly evolving AI landscape, evaluating new models, frameworks and platform capabilities, and translating emerging potential into actionable patterns for the organisation.
• Champion responsible AI principles across every solution and team you engage with, ensuring outputs are fair, explainable, and aligned to our governance framework.

• Deep, hands‑on engineering experience with AI technologies including large language models, generative AI and agentic systems.
• Proficiency in Python and modern cloud‑native development practices (Azure preferred).
• Practical experience with prompt engineering, retrieval‑augmented generation (RAG), fine‑tuning, and AI orchestration frameworks such as Lang Chain, Semantic Kernel, or equivalent.
• Strong understanding of data engineering fundamentals and how AI solutions interact with data platforms, pipelines, and governance.
• Experience operating across large‑scale enterprise environments, navigating security, compliance, and integration complexity.
• Familiarity with Sainsbury's strategic platforms (Snowflake, Azure, AWS,…