Sainsbury's
Staff AI Engineer (AI Specialist)

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Staff AI Engineer
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.
What you need to do
- 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.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
What you need to know
- 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 LangChain, 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, Microsoft 365 Copilot) is advantageous.
- Awareness of responsible AI principles and practical experience applying them in delivery contexts.
What you need to show
- A track record of engineering impact at organisational scale, not just team level. You have made other engineers and teams more effective, not just delivered your own work.
- Ability to move from ambiguous problem statements to working solutions at pace, comfortable operating in uncertainty and converging through experimentation.
- Strong technical communication skills, able to translate complex AI concepts clearly for non-technical stakeholders and articulate trade-offs confidently with engineering peers and architects.
- A genuine drive for knowledge sharing and capability building, actively lifting the AI engineering skills of those around you.
- Excellent collaboration and influencing skills, able to build trust quickly across Product, Engineering, Architecture, Data Science, and leadership.
- Strong judgement on build vs. buy vs. configure decisions, particularly in a fast-moving AI tooling landscape.
- Comfort operating across the full spectrum from low-code AI configuration to deep pro-code engineering, selecting the right approach for each context.
- High levels of technical curiosity balanced with pragmatism, knowing when good enough the right call is and when rigour is non-negotiable.


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What decisions I can make
- Technical approach, architecture, and engineering standards for AI solutions across Sainsbury's Tech.
- Selection and curation of reusable AI patterns, accelerators, and reference implementations.
- Recommendations on feasibility, go/no-go, and scaling readiness for AI proofs of concept.
- Tool and framework selection for shared AI engineering patterns, aligned to strategic platform direction.
Support we will provide
- Access to personal development tools including industry leader Bitesize talks, online self-development tools, and internal mentoring/coaching.
- Direct access to Sainsbury's AI and Data platforms, tooling, and cloud infrastructure.
- A collaborative environment working alongside Product, Architecture, Data Science, and Engineering leadership.
- Opportunities to attend external AI/ML events and conferences.
- Technical development resources, including access to relevant learning platforms, certifications, and emerging technology previews.
Benefits
- Generous colleague discount across Sainsbury's, Argos, and Habitat
- Competitive holiday allowance
- Private Health Care
- Bonus scheme
- Pension plan
- Flexible / smarter working policy
- Access to special offers on gyms, restaurants, holidays, retail vouchers and more
Work-life balance matters to us. We offer flexibility in how, when, and where you work, combining remote collaboration with the right balance of freedom to support your life outside work.
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