Senior Search Engineer - Kotlin / ElasticSearch

Sainsbury's
London
1 year ago
Applications closed

Related Jobs

View all jobs

Senior Machine Learning Engineer, Search & Recommendations

Senior Machine Learning Scientist - Search

Senior Machine Learning Engineer (AI Foundation)

Senior Data Scientist

Senior Data Scientist

Head of Machine Learning (Recommendations, AI Stylist & Search)

We’re a multi-channel, multi-brand business serving millions of customers a day, with the UK’s largest loyalty scheme and an ever-evolving set of digital platforms. All of this equals over 1.2 billion transactions each year, presenting a volume, depth, and complexity of data that few can match.

We don’t think we’re exaggerating when we say we have the most exciting data set in the country. From the insights gained, we build scalable, high-performance products using cutting-edge technology that give our customers an amazing shopping experience – like our award-winning Smartshop app. In an inclusive, agile environment, you’ll have the space to be curious, to experiment, and to solve real-world challenges. And you’ll get to see your creations in the hands of millions of people across the UK.

As Senior Engineer, you’ll be part of one of our Engineering teams, applying architectural and engineering principles to define and deliver technology that will better customer experiences, improve efficiency, and reduce business costs, helping us to lower prices. You’ll support your team by enabling performance, compliance, and risk management by sharing your expertise, judgment, and passion for delivering quality products for customers.

The role

We are looking for a Senior Software Engineer to grow our Search and Product Recommendations Platform team. It is an autonomous, agile product development team building microservices that ensure the results of our customer searches across our multiple brands and channels are accurate and relevant. The team builds high performing microservices by interpreting and following best practice architectural and engineering principles, operating frameworks, and modern tech solutions. This is a fantastic opportunity to work in a domain where we have a huge impact on millions of our customers and drive significant incremental sales for our business.

More about the role

Coding in Java/Kotlin with tools and frameworks like Spring Boot and Gradle. Working on cloud and container technologies such as EMR on AWS (where we train some of our machine learning models) and Kubernetes (where we deploy our APIs). Producing test-driven features and demonstrating your familiarity with the TDD cycle. Lead the design, development, and ultimately operation of the search and recommendations engine at scale. Be responsible for the quality, performance, and stability of the system. Work with other teams to identify, troubleshoot, and resolve high impact issues. Write high quality code, automated tests, and adhere to engineering best practices. Identify and guide the adoption of best practices in code development, continuous integration (CI), testability, and maintainability Propose and implement new features based on an analysis of customer requirements, industry trends, and competitive offerings

More about you

Commercial experience developing in Java/Kotlin(preferable). Experience with Elasticsearch or a NoSQL document store. Experience with AWS cloud. Experience with building Event driven applications with the likes of Kafka. Proven experience in software design and implementation, security, cloud, infrastructure as code and CI/CD, and any relevant hardware  Drive for advocacy of agile/lean delivery methodologies  A passion for delivering solutions to customers, owning the whole software development lifecycle, and living the DevSecOps principles. A passion for enhancing your knowledge and evidence curiosity in emerging tech. Display empathy and understanding in supporting colleagues in the team to deliver. Good spoken and written English.

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.