Head of Engineering & Product Delivery – Pricing, Modelling & Accumulation

Description

You will set the engineering vision and technical roadmap for the Pricing Modelling & Accumulation P&C domain shape delivery priorities with product and business counterparts and lead the end-to-end delivery of integrated platforms that support critical P&C business capabilities.

The Head of Engineering & Product Delivery ensures that business priorities are translated into technically sound product and platform outcomes that architecture and engineering decisions align with strategic goals cross-team dependencies are actively managed and that delivery results in a coherent resilient and maintainable technology landscape.

You will work closely with business product architecture data AI risk and engineering teams. Your role is to provide the technical leadership product delivery discipline and cross-functional coordination needed to turn complex business objectives into scalable and reliable platforms that generate measurable value.

The challenge in this domain is not simply building features. It is leading engineering across multiple teams and technical components while preserving architectural integrity product coherence operational resilience maintainability and business relevance.

This role is critical because the domain depends on strong engineering leadership pragmatic architecture data and model integration technical dependency management delivery discipline and continuous improvement across a complex P&C technology landscape.

Responsibilities

• Define and drive the engineering vision technical strategy and roadmap for the Pricing Modelling & Accumulation P&C domain in close partnership with product and business leadership.

• Lead the end-to-end engineering delivery of integrated platforms services data flows and model execution capabilities that support critical P&C business outcomes.

• Translate business priorities and product objectives into engineering roadmaps delivery plans technical designs and implementation approaches.

• Ensure platforms evolve as one coherent product and technology landscape rather than a collection of disconnected applications services or data flows.

• Establish engineering governance architecture guardrails product delivery practices and execution disciplines that support predictable scalable and high-quality outcomes.

• Manage technical and delivery dependencies risks priorities and trade-offs across teams to ensure smooth and coordinated execution.

• Provide senior leadership on solution design architecture engineering standards and key technology decisions.

• Ensure strong alignment between data models business rules APIs integration patterns and business applications.

• Partner closely with business product architecture data AI risk and engineering teams to align outcomes sequencing trade-offs and execution.

• Drive decision-making and resolve delivery challenges ensuring progress against agreed objectives timelines quality standards and operational expectations.

• Balance business value user needs technical feasibility architectural integrity operational resilience and long-term sustainability in engineering decisions.

• Drive adoption of AI-enabled practices where they improve engineering productivity platform capabilities model operations and decision support.

• Communicate technical direction product delivery progress risks dependencies and trade-offs clearly to senior stakeholders.

• Promote continuous improvement in engineering practices product delivery Agile ways of working DevOps quality engineering observability and production operations.

• Ensure delivered solutions generate measurable business value and strong product outcomes while remaining secure reliable maintainable and operationally efficient.

• Provide leadership coaching and line management for the Product team including objective setting performance development talent management and capability building.

• Build and maintain a high-performing engineering and product organization with a strong culture of accountability collaboration technical excellence customer focus and risk awareness.

Qualifications

• Bachelors or Masters degree in Computer Science Engineering Mathematics Actuarial Science Data Science Business Product Management or equivalent relevant experience

• Significant experience in software engineering platform engineering technical delivery and engineering leadership

• Proven experience leading large engineering domains including internal teams and external partners

• Experience shaping technical roadmaps delivery plans and product outcomes in partnership with product and business stakeholders

• Strong understanding of modern software architecture cloud platforms APIs integration patterns data platforms and model execution environments

• Strong knowledge of software development best practices Agile methodologies DevOps principles observability production operations and engineering governance

• Experience orchestrating technical and product delivery across multiple squads applications services and cross-functional teams while preserving architectural integrity

• Experience with data-intensive analytical and modelling platforms such as:

• pricing and rating systems

• actuarial catastrophe or probabilistic modelling platforms

• exposure management and accumulation systems

• portfolio analytics and decision-support platforms

• Experience integrating data pipelines analytical models risk assumptions business rules and business applications

• Experience driving modernization platform simplification and engineering operating model improvements

• Practical understanding of AI/LLM opportunities in engineering productivity analytics model operations and decision systems

• Experience in P&C insurance reinsurance pricing modelling exposure management or regulated financial services is a strong advantage

• Fluency in professional and technical English

Required Experience:

Director

Employment Type : Contract
Experience: years
Vacancy: 1