Location
London

Hours
Full Time

Salary
Competitive, commensurate with experience

About the Role
The AI & ML Engineering team at Charlotte Tilbury accelerates the adoption of AI across the business, championing innovation while ensuring our machine learning solutions are robust, scalable, and cost-efficient. You will work on a variety of AI initiatives, contributing to the design, implementation, and deployment of scalable AI systems. This role covers the full AI/ML engineering lifecycle, from discovery to deployment and monitoring, including agentic systems development and conventional ML engineering for use cases such as recommender systems and forecasting models.

Key responsibilities include designing and implementing agentic systems using techniques like RAG, grounding, prompt engineering, and orchestration on a GCP-first stack; building and maintaining production ML pipelines and services; developing APIs and microservices ensuring security, scalability, and observability; implementing CI/CD for ML services and infrastructure as code; establishing robust guardrails for safe AI usage; contributing to reusable components, documentation, and best practices; collaborating with cross-functional teams; and supporting the evaluation of new AI technologies and frameworks.

This role reports to the Lead AI & ML Engineer and is part of the Data function, working within a specialist AI engineering team alongside colleagues from Technology, Data, and Product. Charlotte Tilbury is a fast-paced, dynamic environment where agility, ambition, and passion for excellence help teams thrive. We seek individuals eager to grow, innovate, and contribute to a truly global #DreamTeam.

Experience
- Strong Python engineering skills including FastAPI, testing, and typing
- Hands-on experience with GCP Vertex AI or equivalent cloud-native AI/ML platforms (AWS SageMaker, Azure ML)
- Experience with agent orchestration frameworks such as LangChain, LangGraph, ADK
- Solid understanding of MLOps including CI/CD, Infrastructure as Code (Terraform), experiment tracking, model registry, and monitoring
- Proven experience deploying and operating ML systems in production (batch and real-time)
- Familiarity with RAG architectures, prompt engineering, guardrails, and evaluation techniques
- Experience developing agentic capabilities such as agent skills, MCP servers, and tool usage
- Strong grasp of security, privacy, and governance principles including IAM, secrets management, and PII handling
- Effective communication skills to work with both technical and non-technical stakeholders
- Interest in evaluating new AI technologies and contributing to technical discussions

About you
You are passionate about building production-ready AI and machine learning solutions, with a blend of technical depth and product sense. You thrive in collaborative environments and are motivated to contribute to continuous improvement and innovation. You are adaptable, eager to learn, and excited to work in a fast-paced, high-growth company.

Qualifications
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or demonstrable relevant experience.

Desirable
- Knowledge of vector databases and retrieval strategies
- Experience with recommender systems and ranking models
- Familiarity with LLM evaluation tools such as RAGAS, TruLens, LangSmith, Arize
- Working understanding of cloud networking and platform infrastructure
- Experience in e-commerce or retail environments