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# Software Engineering Lead / Applied AI Engineering

- **Company:** RELX Group
- **Location:** London, UK
- **Experience:** Expert
- **Salary:** £74,676.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Software Quality, Cyber Security, DevOps, Distributed Systems, Python (Programming Language), Machine Learning, Software Engineering, Large Language Models, Snowflake, Apache Spark, Backend, Machine Learning Operations, Databricks
- **Published:** August 14, 2026
- **Apply:** https://www.adzuna.co.uk/jobs/details/5838452275

## About the Role

* 7+ years in backend, full-stack, ML engineering, or distributed systems.
 * 2+ years in technical leadership, team leadership, or senior mentoring roles.
 * Hands-on experience deploying ML-powered services into production.
 * Strong Python and Java, both of which are in active use across the team's production services.
 * Experience with Snowflake, Spark, Databricks or similar technologies, CI/CD pipelines, and modern DevOps tooling.
 * Solid understanding of SecOps practices and security-conscious system design.
 * Demonstrable track record of taking initiative and driving work independently.
 * Broad full-stack curiosity, with the ability to contribute outside a primary discipline when needed.

Risk benefit statement

## Description

As a technical leader, you will guide a multidisciplinary engineering team responsible for delivering AI-enhanced products, internal tools, and platform capabilities. You will combine hands-on technical expertise with people leadership, helping the team build scalable, secure, and reliable machine learning services while driving innovation and operational excellence., * Lead and grow a team of full-stack ML engineers, QA engineers, and a UI developer.

 * Define technical direction for AI-enhanced services, internal tools, and platform components.
 * Drive architecture for model deployment pipelines, inference APIs, and data and feature systems.
 * Ensure high-quality delivery across code quality, testing, documentation, and observability.
 * Partner with Product, Architecture, and ML Research teams to prioritise and scope work.
 * Foster a culture of modern AI development practices, including LLM tooling, MLOps, and automation.
 * Set and enforce DevOps and SecOps standards across the team's services and pipelines.
 * Coordinate cross-team dependencies and contribute to roadmap planning.


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