Staff AI/ML Engineer (£130,000–£160,000 + Equity) at Tech-forward insurance platform

Title

Staff AI/ML Engineer (£130,000–£160,000 + Equity) at Tech-forward insurance platform

Job Title

Staff AI/ML Engineer

Salary

£130,000–£160,000 + Equity

Company Description

Tech-forward insurance underwriting platform

Job Description

As the first AI/ML hire, you will architect and build intelligent systems from the ground up to transform specialty insurance. Working directly with the CTO, you will own the full technical strategy—from MLOps infrastructure to production RAG systems that augment expert decision-making and surface critical portfolio insights in a legacy industry.

Location

London, UK

Why this role is remarkable

• You are the founding AI hire with complete autonomy to define the technical roadmap and architectural choices without legacy constraints.
• Join a well-funded startup led by industry veterans at the intersection of traditional Lloyd’s market expertise and cutting-edge machine learning.
• Tackle high-impact, greenfield challenges using messy, real-world data to build systems that provide a genuine competitive advantage in a trillion-dollar industry.

What You Will Do

• Design and deploy production-grade AI systems, including RAG architectures for natural language querying and automated risk signal models for underwriters.
• Build and own the entire ML infrastructure stack, establishing MLOps practices, experiment tracking, and deployment pipelines from scratch.
• Collaborate with domain experts to identify high-impact AI opportunities across portfolio analytics, claims processing, and operational workflows.

The ideal candidate

• 10+ years of software and ML engineering experience with a proven track record of shipping production-grade systems that users depend on.
• Deep expertise in LLM-based systems, RAG architectures, and traditional ML techniques like anomaly detection and time-series forecasting.
• Strong engineering foundations in cloud infrastructure, API development, and CI/CD, with a pragmatic approach to balancing innovation and stability.

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