At a Glance
- Tasks: Lead AI projects, design prototypes, and experiment with cutting-edge technologies.
- Company: Join The Economist Group, a leader in innovation and analytical insights.
- Benefits: Enjoy competitive pay, health insurance, flexible work options, and access to exclusive content.
- Other info: Collaborate in a dynamic team with excellent growth opportunities.
- Why this job: Shape the future of AI in journalism and make a real impact.
- Qualifications: Experience with generative AI, strong engineering skills, and a passion for innovation.
The predicted salary is between 80000 - 100000 £ per year.
We are an organisation that exists to drive progress. Our businesses share a devotion to innovation, independence and rigour in their fields of expertise. We empower people to understand and tackle the critical challenges and changes facing the world. Our analytical rigour, global expertise and evidence-based insights enable individuals and organisations to make sense of these shifts and chart a course through them.
This is a permanent, senior role within the AI Lab that will help shape and build the next generation of AI-powered Economist experiences. This hire will play an especially important role over the next 6 to 12 months, providing senior technical leadership and continuity while our current Technical Lead is on maternity leave. After that period, they will remain a core senior member of the Lab, helping shape its technical direction and lead the development of future prototypes and AI innovation.
This is a hands-on role for someone who combines strong engineering judgement with deep familiarity with modern AI systems. You will help turn promising ideas into working prototypes, assess emerging technologies, and guide technical decisions across the AI Lab’s work. You should be comfortable operating in an exploratory environment where not every question has a clear answer, but where disciplined experimentation and practical delivery matter. This role will be based in our London headquarters.
Responsibilities
- Provide senior technical leadership for the AI Lab’s work, ensuring continuity and momentum during a period of maternity cover.
- Design, build and iterate on prototypes and experimental concepts using frontier AI capabilities across areas such as text, audio, voice, video and multimodal experiences.
- Lead technical investigation and experimentation, including testing new models, methods and workflows.
- Partner with commercial, editorial and other technology teams to support the testing, scaling and launch of concepts developed by the AI Lab.
- Shape and implement the right technical architectures for AI Lab prototypes and experiments - balancing speed, quality, flexibility and longer-term scalability.
- Help the Lab identify where advances in AI could create distinctive value for Economist audiences and products.
- Contribute to the Lab’s longer-term technical direction, helping decide what capabilities to build, test or scale over time.
- Support and, where appropriate, mentor other technical contributors working on Lab initiatives.
What sort of person we are looking for
- A strong technical builder with deep curiosity who enjoys turning emerging ideas into tangible products and prototypes.
- Comfortable taking ownership and being autonomous in an uncertain, fast-moving environment.
- Works well in a small team with the freedom to make decisions and communicate clearly with others.
- Combines technical knowledge with business sense to ensure that research supports company goals and editorial standards.
- Able to switch between hands-on engineering, technical strategy and clear communication with non-technical colleagues.
- Understands The Economist’s core values of classical liberalism, intellectual rigour and editorial independence.
Specific skills and expertise
- Significant experience building with modern generative AI models and systems in production or advanced prototype settings.
- Strong software engineering skills, with the ability to design and implement robust prototypes quickly and thoughtfully.
- Experience working across multiple modalities such as text, audio, voice, video or conversational interfaces.
- Good judgement in selecting and evaluating models, tooling and system architectures for different use cases.
- Ability to explain technical concepts, opportunities and constraints clearly to non-technical audiences.
- Experience defining practical evaluation approaches for AI systems, including quality, reliability and usability.
Strong candidates might also have
- Experience in a startup, innovation, advanced product or R&D environment.
- Experience in building B2C customer-facing AI products or features in content-rich or editorial domains.
- Interest or experience in media, journalism, information products or knowledge-rich domains.
- Familiarity with fine-tuning, benchmarking, model evaluation and experimentation workflows.
- Experience with orchestration frameworks, tool-using systems and agentic patterns.
- Experience leading senior technical work during periods of ambiguity, change or team transition.
How to submit an application
Candidates should submit a CV and optional cover letter.
More about the Economist AI Lab:
We believe AI will fundamentally change both our business and the world around us, making our mission more vital than ever. While we already use AI across The Economist Group, we think the changes to come in the next few years could be even more far-reaching. This is why we have established the Economist AI Lab–to reimagine Economist journalism for an AI-driven world.
Working Arrangements
The majority of our roles operate on a hybrid working pattern, with 3+ days office attendance required.
AI usage for your application
We are an innovative organisation that encourages the use of technology. We recognise that candidates may utilise AI tools to support with their job application process. However, it is essential that all information you provide truthfully and accurately reflects your own experience, skills, and qualifications.
What we offer
Our benefits package is designed to support your wellbeing, growth, and work-life balance. It includes a highly competitive pension or 401(k) plan, private health insurance, and 24/7 access to counselling and wellbeing resources through our Employee Assistance Program. We also offer a range of lifestyle benefits, including our Work From Anywhere program, which allows you to work from any location where you have the legal right to do so for up to 25 days per year. In addition, we provide generous annual and parental leave, as well as dedicated days off for volunteering and even for moving home. You will also be given free access to all The Economist content, including an online subscription, our range of apps, podcasts and more.
Lead AI Engineer, AI Lab employer: Dormont Manufacturing Co
At The Economist Group, we pride ourselves on being an exceptional employer that fosters innovation and independence within a collaborative work culture. As a Lead AI Engineer in our London headquarters, you will have the opportunity to shape the future of AI-driven journalism while enjoying a comprehensive benefits package that supports your wellbeing and professional growth, including flexible working arrangements and access to exclusive content. Join us in driving progress and tackling the world's critical challenges in a dynamic and supportive environment.
StudySmarter Expert Advice🤫
We think this is how you could land Lead AI Engineer, AI Lab
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We think you need these skills to ace Lead AI Engineer, AI Lab
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Dormont Manufacturing Co.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Dormont Manufacturing Co and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Dormont Manufacturing Co
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Dormont Manufacturing Co uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.