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WeDoTech in London is seeking a Senior Applied AI Engineer to own production LLM systems, focusing on real-world problems and scalable deployments. You will collaborate with Product to improve quality, cost and latency, and shape new features for a production-ready AI platform.
The role emphasizes hands-on engineering, AI-native tooling, and delivering robust, production-grade solutions in a hybrid London office environment.
Salary: Up to £140,000 base
Location: London - Moorgate | Hybrid, 2 days per week in the office
Work Type: Permanent
Role: We're working with an exciting AI technology business looking for a Senior Applied AI Engineer to join the team building and improving its production LLM systems. This is a hands-on engineering role for someone who wants to work on real-world AI problems where the technology is already being used in production. Rather than focusing on training models or open-ended research, you'll be solving the challenges that come with making LLM-powered products genuinely work at scale. You'll have the opportunity to influence how the product evolves, working closely with Product to improve quality, reduce cost and latency, build better evaluation frameworks and solve real production failures. The engineering environment is also heavily AI-native, with tools such as Claude Code forming a key part of how the team builds and ships software.
This is an opportunity to move beyond LLM prototypes and work on the difficult engineering problems that appear when AI systems are operating in a real production environment. You'll be able to see the impact of your work directly – whether that's improving the quality of outputs, making the platform faster and more cost-effective, solving production issues or influencing what gets built next. You'll also be joining an engineering environment that actively embraces AI-native development rather than simply experimenting with it on the side. If you're an experienced software engineer who has already shipped LLM systems and you want your next role to combine hands‑on engineering, applied AI, product influence and genuine production challenges, this could be a great next step.