Overview
Applied AI Engineer - AI Product Deployment | High-Growth Tech Company
London - Hybrid - 3 days a week in the office
Up to £125,000 per annum plus bonus and stock
Applied AI Engineer - We’re working with a fast-scaling, venture-backed AI and technology business that partners with leading organisations to embed AI capability into the workforce at scale. Their products are already used by thousands of learners and enterprises, and they’re now doubling down on operationalising AI in production.
They’re hiring an Applied AI Engineer to focus on deploying, integrating, and scaling AI and LLM-powered systems inside real products. This is not a research or pure model-development role — it’s for engineers who enjoy taking models that already exist and making them reliable, observable, and valuable in the real world.
The role
The Applied AI Engineer will join a brand new team, sitting at the intersection of product engineering, AI and platform engineering. You’ll work closely with Product, Design and Data teams to turn AI capabilities into dependable, user-facing features.
Key responsibilities
- Deploying and integrating AI models (including LLMs) into production systems and user-facing products.
- Designing and implementing LLM-powered workflows for use cases such as content generation, semantic search, summarisation, and personalisation.
- Building APIs, services and pipelines that enable AI features to run at scale, securely and reliably.
- Owning the end-to-end delivery of AI features: from experimentation and integration through to launch, monitoring, and iteration.
- Establishing strong MLOps practices, including deployment pipelines, monitoring, evaluation, rollback strategies, and retraining workflows.
- Measuring feature performance, latency, accuracy, cost, and adoption — and improving based on real usage.
- Acting as a bridge between technical and non-technical teams, helping others understand what AI can (and can’t) do in production.
What they’re looking for
- Strong experience deploying machine learning or LLM-based systems into production.
- Hands-on experience working with LLMs (e.g. GPT, Claude, Gemini), including prompt engineering, orchestration, evaluation and safety considerations.
- Excellent software engineering skills in Python with experience building APIs and backend services.
- Practical experience running AI systems on AWS, including CI/CD, model versioning, monitoring, and observability.
- Familiarity with MLOps concepts such as deployment pipelines, model monitoring and retraining (rather than model research).
- Experience working with structured and unstructured data in production environments.
- A product-focused mindset — you care about usability, performance, reliability, and real-world impact.
- Comfortable collaborating closely with Product, Design and Data teams.
- Experience with modern AI tooling platforms (e.g. Cursor, Gemini) is a strong advantage.
This is a fantastic opportunity for an Applied AI Engineer to join a new team in a high-growth company. Please reply with your CV or call Simon for a chat.
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