VP Engineering​/CTO

Salary:
Basic circa £150,000–£185,000 depending on level and experience, plus bonus, benefits and stock options

Azur Technology is evolving into a product‑led, AI‑augmented SaaS provider for the MGA (Managing General Agent) market. Following a successful private funding round, we are reimagining how insurance technology is built.

Our flagship product, MGA Connect, is a modern SaaS platform designed to replace legacy, 90s‑era technology with a lean, highly configurable system.

We are looking for a leader to bridge the gap between our established Salesforce‑based architecture and a future defined by AI‑driven development efficiencies — while also owning the broader technology strategy as we scale.

This is a high‑impact leadership position for a technical strategist who recognises that AI is fundamentally changing the engineering landscape.

You will lead a global team of 50+ engineers (headquartered in London, with a significant hub in the Philippines), transitioning the culture from traditional development cycles to a high‑performing, AI‑enabled operation.

In addition to engineering leadership, this role expands into CTO‑level accountability – owning platform strategy, technical operations, and security as we scale into a mature SaaS business.

As we enter a new phase of growth and AI adoption, this role and person will build and run a high‑performing product engineering organisation that delivers reliably, scales efficiently, and supports the transition to a product‑led SaaS model.

• Build and lead a scalable engineering organisation
• Define team structures (squads/pods aligned to product areas)
• Hire, develop, and retain high‑quality engineering talent
• Establish clear ownership, accountability, and leadership layers

• Own predictable, high‑quality delivery
• Implement strong planning and estimation practices
• Establish sprint and release discipline
• Introduce delivery tracking and reporting
• Shift the culture from ad hoc delivery to a repeatable execution engine

• Partner closely with Product to align engineering to roadmap and priorities
• Ensure teams are working on reusable, scalable product features
• Drive a mindset shift from client‑specific builds to productised capabilities

• Embed AI into engineering workflows, including:
  • Developer productivity (copilots, automation)
  • Testing and QA acceleration
  • Documentation and knowledge sharing
• Reduce dependency on linear team scaling
• Evolve towards AI‑assisted / agentic delivery models
• Stay abreast of changes in the AI landscape and adopt relevant improvements

• Establish and enforce an automation‑first testing strategy
• Implement strong CI/CD discipline
• Define and uphold code quality standards
• Improve reliability, maintainability, and release confidence

• Define and track key engineering metrics, including:
  • Delivery predictability
  • Cycle time / lead time
  • Deployment frequency
  • Defect rates / quality
• Use data to drive continuous improvement

• Own the reliability, performance, and scalability of the production platform
• Establish best practices across:
  • Infrastructure management (cloud, environments, cost optimisation)
  • Monitoring, alerting, and incident management
  • Disaster recovery and business continuity planning
• Ensure high availability and resilience of customer‑facing systems
• Drive Dev Ops maturity, including environment strategy and release management
• Partner with Engineering and Product to ensure operational readiness for new features
• Balance performance, cost, and scalability as the platform grows

• Own the overall security posture of the platform and engineering practices
• Ensure compliance with key frameworks and standards (e.g. SOC 2, ISO 27001, GDPR)
• Embed security‑by‑design principles into architecture and development workflows
• Implement secure SDLC practices, including code scanning and vulnerability management
• Define and enforce data protection, access control, and encryption standards
• Lead incident response and ongoing…