Applied AI Engineer
Highlights
* UK-based startup backed by a
£100m investment
* Building an AI-first product and engineering organisation from the ground up
* Founding-level opportunity with significant influence on technical direction and strategy
* Highly competitive compensation, with current conversations ranging from
£120k-£400k+
, plus equity. We are looking for the very best candidates to work with some exceptional talent
* 100% remote, with an option to go to a London office if wanted
* Multiple live openings across AI, Engineering, Research, Platform, and Leadership
About the Company
The company is building an AI-native smart assistant designed to help everyday users manage conversations, tasks, organisation, and workflows with minimal prompting. The focus is on creating highly reliable AI systems capable of long-running workflows, persistent context, multi-step reasoning, and real-world task completion.
The aim is to significantly reduce the time users spend completing daily tasks through intelligent automation.
The Role
As an
Applied AI Engineer
, you will be responsible for transforming AI model capabilities into real-world product functionality. You'll own problems end-to-end, working across machine learning, systems engineering, and product development to ensure AI solutions operate reliably in production environments.
This role focuses on delivering AI products that work effectively for users at scale—not just in demonstrations.
Key Responsibilities
* Build and deploy AI-powered features from model development through to user experience.
* Design and improve prompts, tools, memory systems, and agent workflows.
* Convert raw model outputs into structured, reliable behaviours.
* Debug and resolve issues across the full stack, including models, orchestration, infrastructure, and user experience.
* Optimise AI systems for latency, reliability, and cost efficiency.
* Develop evaluation frameworks to measure real-world performance.
* Collaborate closely with Product and Engineering teams to solve complex problems and deliver working solutions.
Technology Stack
* Python
* PyTorch
* JAX
* Large Language Models (OpenAI APIs, Llama, Qwen, etc.)
* Inference and Serving Frameworks (e.g. vLLM)
* Vector Databases
What We Look For
* Hands-on engineering ability, not just AI strategy or management experience.
* Experience building AI agents, LLM apps, RAG systems, automation workflows, copilots or AI-enabled tools.
* Strong coding ability in Python, TypeScript, JavaScript or similar practical stack.
* Good judgment on what should be automated and what should not.
* Able to ship working systems, test quality and improve reliability over time.
* Fintech, banking, support automation, risk, KYC, fraud, CRM or operations automation experience is a strong plus.
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