We're exclusively partnered with a fast-scaling, AI-first SaaS company developing cutting-edge commercial intelligence tools used by global brands. Their platform empowers clients to optimise product ranges and design AI-powered shopper journeys.

Now looking for an AI Engineer to lead the design and deployment of production-grade ML and LLM systems, with a strong focus on data engineering, MLOps, and scalable backend infrastructure.

What You’ll Be Doing

Building and maintaining end-to-end MLOps pipelines (CI/CD, versioning, monitoring)
Developing backend APIs and systems to serve ML and LLM models in production
Scaling big data infrastructure using tools like Airflow and DBT
Deploying on cloud (Azure preferred, GCP accepted), with Docker and Kubernetes
Driving research and integration of modern ML and LLM techniques into the product
Working closely with the Data Scientist, SVP of Tech, and wider product and engineering teams

What They’re Looking For

3+ years in Data Engineering or MLOps roles, with exposure to LLMs
Strong Python skills and familiarity with PyTorch, Hugging Face, Scikit-learn
Experience with Airflow, DBT, Docker, Kubernetes, and RESTful API development
Cloud experience
Comfortable working in a fast-paced, collaborative, startup environment

Nice to Have

LLM fine-tuning experience
Kafka, Flink, Snowflake or similar
Retail or consumer goods industry experience
Contributions to open-source or ML/AI research

This is a hands-on role reporting into the SVP of Tech, with real ownership and a direct line to leadership. The company is profitable, recently funded, and targeting rapid growth.

We’re looking to move quickly, with interviews already underway. September start ideal, two-month notice max.

Apply with your CV below!