Generative AI Engineer - GCP & LLMs for Insurance

Brown & Brown Insurance; Greater London; Hybrid; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Holiday entitlement

Company pension

Flexible working

Funding for professionalQualifications

Job summary

Brown & Brown Insurance is seeking an AI Engineer to design, build, and deploy Generative AI solutions on Google Cloud Platform (GCP), integrating LLMs such as ChatGPT and Claude for insurance use cases. The role is hybrid and London-based, focused on moving AI from prototype to production while collaborating with risk, compliance, and data teams.

You should have strong Python, MLOps, RAG, and vector database experience, plus hands-on work with Vertex AI and containerised deployments.

Qualifications

• Degree in CS, Engineering, AI or related field.
• Production-grade Python development experience.
• Experience deploying AI services via APIs and building backend services.
• Familiarity with CI/CD, testing, and modern software practices.

Responsibilities

• Design, build, and deploy AI-powered applications for insurance use cases.
• Develop and deploy AI solutions on Google Cloud Platform (Vertex AI, BigQuery, Cloud Run).
• Implement CI/CD, monitoring, logging, and model performance tracking for AI solutions.
• Ensure Responsible AI, data privacy, and governance considerations are addressed.
• Collaborate with Product Owners, Underwriters, Brokers, Operations and Tech teams to translate business problems into AI solutions.

Skills

Python development

API integration

CI/CD

LLMs

ChatGPT/OpenAI API

Prompt engineering

RAG architecture

Vector databases

Education

Bachelor's degree in Computer Science or related field

Tools

Google Cloud Platform (GCP)

Vertex AI

Docker / containerised workloads

Job description

Brown & Brown Insurance is seeking an AI Engineer to design, build, and deploy Generative AI solutions on Google Cloud Platform (GCP), integrating LLMs such as ChatGPT and Claude for insurance use cases. The role is hybrid and London-based, focused on moving AI from prototype to production while collaborating with risk, compliance, and data teams.

You should have strong Python, MLOps, RAG, and vector database experience, plus hands-on work with Vertex AI and containerised deployments.