Staff Product Engineer

Overview

Join hx as Staff Product Engineer to shape the technical direction of the Model Authoring platform. You will own standards, interfaces, and shared enablers that govern how pricing models are created, reviewed, and deployed. This is hands-on work at the highest-risk areas, with a strong emphasis on AI-native approaches and cross-team collaboration. You will mentor peers and push for credible, trustworthy product experiences in a rapidly scaling insurtech. This is your chance to influence how a global platform enables insurers to move faster and price with confidence.

Pay / Benefits

• 5,000 training and conference budget
• 33 days holiday (25 days + 8 bank holidays)
• Private healthcare insurance
• Company pension scheme
• Mental health support and therapy
• Cycle to Work Scheme

Responsibilities

• Establish engineering standards across the Model Authoring pods and ensure they are referenced in code reviews
• Own the technical direction for shared enablers (model representation/persistence, model registry, secure context access, shared agentic infrastructure)
• Define technical interfaces between Model Authoring and other business areas; align dependencies with other teams
• Hands-on work on the hardest problems in the stream, not solely advisory
• Help shape the AI-native approach to model development and determine what to hand to agents vs. humans and what evidence is needed for trust
• Mentor engineers and contribute design input across pods to raise the technical bar

Key requirements

• Experience in AI-native environments and using AI/agentic tools in engineering workflows
• Product-focused mindset with understanding of user pain points and business impact
• Proven track record of owning architecture in a domain with no established playbook and making calls under ambiguity
• End-to-end ownership of a significant technical challenge or service, with understood trade-offs and contracts
• Influence across teams and ability to persuade and align stakeholders
• Experience working across distributed teams (Warsaw and London)

• Influence and persuasion
• Cross-functional collaboration
• Mentoring and coaching
• AI-native software development
• System architecture ownership
• Defining interfaces between services/teams

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