ML / AI Platform Engineer

United Kingdom·Londonmid

OtherAi Platform Engineer

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Quick Summary

Overview

Why join us At Sainsbury's, we're investing in shared AI and machine learning platforms that enable teams across the business to build, deploy and operate intelligent solutions safely,

Technical Tools

OtherAi Platform Engineer

What We Offer

~3 min read

At Sainsbury's, we're investing in shared AI and machine learning platforms that enable teams across the business to build, deploy and operate intelligent solutions safely, securely and at scale.

You'll help shape the engineering foundations that power machine learning, generative AI and agentic applications across the organisation. Working as part of a platform engineering team, you'll build reusable capabilities that make it easier for product teams, data scientists and engineers to deliver value while meeting our standards for security, reliability, governance and cost efficiency.

Our platforms include:

✓Azure Machine Learning

✓AI Gateway capabilities built on Azure API Management

✓Shared patterns and tooling for agentic and generative AI solutions

✓Core platform services covering identity, networking, observability, security, deployment and cost management

✓Generous colleague discount across Sainsbury’s, Argos, and Habitat

✓Competitive holiday allowance

✓Bonus scheme

✓Pension plan

✓Flexible / smarter working policy

✓Access to special offers on gyms, restaurants, holidays, retail vouchers and more

Responsibilities

~1 min read

→Design, build and operate shared platform capabilities that enable teams to develop and deploy ML and AI solutions efficiently and securely
→Create reusable infrastructure, tooling and automation that improves the developer experience and reduces operational overhead
→Build and maintain cloud-native platform services covering deployment, networking, security, identity, monitoring and governance
→Collaborate with product teams, data scientists and ML/AI Ops engineers to understand requirements and provide scalable platform solutions
→Drive engineering excellence through automation, standardisation, observability and reliability practices
→Contribute to the evolution of our AI and ML platform strategy, ensuring solutions remain secure, resilient and cost-effective
→Troubleshoot complex technical issues across cloud services, infrastructure and applications
→Support and mentor engineers within the team, sharing knowledge and driving continuous improvement

Requirements

~1 min read

Experience building, operating or improving cloud platforms in AWS, Azure or GCP
Strong understanding of infrastructure as code
Strong programming skills, with experience developing production-quality solutions in Python or other modern programming languages
Experience with CI/CD pipelines, Git-based workflows and modern software delivery practices
Knowledge of cloud networking, identity management, security and access controls
Experience managing containerised workloads and cloud-hosted application platforms
Strong troubleshooting and problem-solving skills across infrastructure and application layers
Experience building reusable platform capabilities and self-service engineering solutions
Ability to lead technical initiatives and take ownership of delivery outcomes
Strong collaboration and communication skills, with a willingness to coach and support others
A growth mindset, with the ability to learn new technologies and apply sound engineering principles in unfamiliar domains

Experience with Microsoft Azure platform services
Azure Machine Learning
Azure API Management
Azure OpenAI, Azure AI Foundry or related AI platforms
Platform Engineering and Developer Experience practices
MLOps, model deployment and model lifecycle management
Experience operating platforms in large-scale enterprise environments
Knowledge of generative AI architectures, AI gateways, agent frameworks or agentic delivery patterns

Engineers can quickly and safely build and deploy ML and AI solutions using shared platform capabilities
Platform services are secure, reliable, observable and cost-effective
Reusable patterns and automation reduce duplication across teams
Platform adoption grows through a great developer experience and strong engineering partnerships
AI and ML workloads can be operated confidently at enterprise scale