AI Platform Engineer (GCP)

AI Platform Engineer (GCP)

Location: London (Hybrid 1-2 Days in Office)

Salary: £100,000 + Benefits

This is a rare opportunity to shape the foundations of an AI function at a pivotal moment in a company's transformation. You will play a lead role in building production-ready AI systems that automate complex insurance journeys, with the freedom to influence architecture, engineering patterns and long-term strategy.

The Company

They are a fast-growing, tech-led insurance provider specialising in complex and non-standard risk. Their products are powered by a blend of smart technology and human expertise, enabling faster decisions, tailored coverage and scalable customer support.

With investment backing and a newly formed AI leadership team, they are now embarking on the next stage of their journey to become an AI-driven insurer. This role represents one of the first senior hires into their AI team.

The Role

You will be responsible for:

• Build and operate production-grade AI agents on GCP using Google's ADK.
• Integrate AI systems with policy, claims and CRM platforms through secure REST and JSON API services.
• Develop scalable RAG pipelines including ingestion, text processing, metadata handling and vector search.
• Implement observability and evaluation frameworks covering monitoring, A/B testing, accuracy and safety metrics, and cost and latency dashboards.
• Contribute to architecture, engineering standards and AI product direction in partnership with the Head of AI.
• Support the development of agentic automation across core claims workflows and internal tools.

Your Skills and Experience

• Strong commercial experience in Data Engineering, ML Engineering or Software Engineering with a focus on AI systems.
• Deep knowledge of GCP services, including Vertex AI, BigQuery, Cloud Run or Cloud Functions, Model Garden and ADK.
• Strong Python skills for backend development, APIs and data processing.
• Hands-on experience with LLMs, embeddings, RAG design, vector databases and retrieval pipelines.
• Experience deploying production AI with robust evaluation, monitoring, observability and automated testing.
• Solid exposure to DevOps tooling including CI/CD, Docker and Kubernetes.

How to Apply

If this sounds like the right next step for you, please apply with your CV to begin the process.