Engineering Lead Catastrophe Risk Modelling Platform (C++)

Engineering Lead Catastrophe Risk Modelling Platform (C++)

KatRisk is a leading provider of catastrophe risk modelling solutions, dedicated to helping businesses and organizations understand, manage, and mitigate the risks associated with natural disasters. Our innovative technology and expertise enable clients to make informed decisions, optimise their risk management strategies, and safeguard their assets and operations against potential catastrophes.

Role Overview : SpatialKat is known for its performance and reliability, we are looking to build on this and transform this world?class modelling engine into a scalable, cloud?native platform while preserving its industry?leading performance. Were seeking a hands?on Engineering Leader with deep C++ expertise to own the reliability, performance, and evolution of our catastrophe risk assessment platform. Youll lead and mentor engineers while contributing code, partnering closely with Data Engineering, Science, and Product to deliver high?impact features and modernise parts of our stack. This platform ingests historical and meteorological data, runs distributed peril?specific catastrophe risk simulations, and supports map?based visualisation and advanced data queries used by enterprise customers. Youll lead a highly skilled team, work cross?functionally with product, science, and data engineering, and drive a strategic transformation : from a high?performance monolith to a scalable, cloud?native system.

Responsibilities

• Own & evolve the core C++ modelling system : maintain, refactor, and enhance an established codebase that drives large?scale peril?specific loss simulations with complex financial modelling.
• Implement new catastrophe risk and financial models as they are designed.
• Modernise the stack : refactor legacy components toward a modular, containerised architecture with improved deployment automation.
• Data?driven simulation accuracy : work with historical and meteorological datasets to ensure scientifically sound, reproducible results in partnership with our Science team.
• Performance & reliability at scale : profile and optimise an I / O?intensive architecture (distributed processes, partial in?memory reads, lz4 binary outputs ~500?MB / core) to meet strict enterprise SLAs both on client?infrastructure environments and as a cloud?based SaaS solution.
• Guide integration with APIs and visualisation components to support new user experiences.
• Distributed compute orchestration : enhance the server?side job scheduler, proxies, and API daemon that coordinate asynchronous batch processing for API clients (including the web front end).
• Modernise the web layer : lead the transition from R Shiny components to a more traditional web stack (IIS / Apache, JavaScript, HTML, CSS) while keeping the system loosely coupled.
• Database stewardship : guide data modelling and performance tuning on our SQL Server backend; ensure data quality, lineage, and operational resilience.
• Engineering leadership : set technical direction, establish coding standards and CI / CD practices, mentor engineers, and drive pragmatic execution across a cross?disciplinary team.
• Security & reliability : strengthen authentication (pluggable approach), observability, and incident response; champion testing and automation throughout the stack.
• Customer impact : collaborate with Product and customer?facing teams to translate enterprise needs into roadmaps, features, client?specific consulting projects, and measurable outcomes.

Tech Stack

Requirements

Required

Preferred

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