Engineering Manager, AI Platform

Who we are

Since 1843, The Economist Group has championed independence, excellence and openness, helping people understand and tackle the critical challenges shaping the world. Today, we are building on that legacy as a global media and information-services company powered by digital innovation, analytical rigour and evidence-based insight.

Across our three businesses - The Economist, Economist Enterprise and Economist Education - we deliver trusted analysis and insights to individuals and organisations in more than 170 countries. United by a shared purpose to drive progress, we empower decision-makers to make sense of change and chart a course through an increasingly complex world.

As a colleague, you will be part of a culture that values ideas, encourages ownership and holds itself to high standards. We invest in people who are curious, thoughtful and adaptable, whether they are launching new products, reporting on global events or harnessing emerging technologies such as AI to improve how we work. Here, fresh thinking is taken seriously, ambition is matched by integrity, and great work is recognised. Working across disciplines, geographies and perspectives, we are united by a commitment to innovation, excellence and creating meaningful impact.

Want to discover more about life at The Economist Group? Follow @EconomistCareers on Instagram to discover the people, stories and opportunities that make TEG unique.

Technology, Product & Data

Our team of 450 colleagues across Technology, Product and Data is at the heart of The Economist Group’s digital-first agenda. Together, we design, build and optimise the digital products, platforms and data capabilities that power our business and reach millions of people around the world. Whether you’re an engineer, product manager, designer, data scientist or analyst, you’ll work on products that have real-world impact. From enhancing economist.com and developing new products for Economist Intelligence to creating personalised experiences and applying AI to solve complex challenges, you’ll help shape how consumers, businesses and government leaders access trusted insights. Working in cross-functional teams, we combine engineering excellence, product thinking and data expertise to solve meaningful problems, experiment with new technologies and continuously improve the experiences we create. It’s an opportunity to do challenging, purposeful work alongside curious, collaborative colleagues, while helping drive sustainable growth for one of the world’s most trusted brands.

The Role

Our AI Platform team builds the technology that powers AI-enabled products and services, for internal users and external customers. We design, build and operate the infrastructure, patterns and reusable capabilities that enable generative and agentic AI, natural language processing, predictive analytics and machine learning across the Group, from customer-facing features in our digital products to the internal tools used by colleagues across our four businesses.

Scope

We are seeking an Engineering Manager to lead our Applied AI and Data Science team: a multidisciplinary group of AI Engineers, ML Engineers, NLP Engineers and Data Scientists. This is a player-coach role. You will own the health, delivery and growth of the team while remaining a hands-on contributor to its work, writing and reviewing code, shaping architecture and stepping into implementation when it matters.

The team’s work spans generative and agentic AI systems built on large language models, alongside the NLP and predictive models that sit behind our products and internal tools. You will turn the Group’s AI ambitions into well-architected, production-grade systems, working in close partnership with the Head of AI and Data Engineering, product managers, data engineers and business stakeholders to decide what we build, why we build it, and how we know it is working. You will also champion the team’s move to AI-native engineering, with coding agents used across the whole software development lifecycle.

Accountabilities

• Lead and manage the team. Provide day-to-day management, mentorship and career development, and build one team across engineering and data science disciplines.
• Own delivery. Own planning, resourcing, prioritisation and delivery with product management, balancing exploratory work against production commitments.
• Communicate progress. Keep…