Head Engineering

Responsibilities: Set engineering strategy - define the roadmap in line with business priorities and lead engineering across all product portfolios. Own technical architecture - guide decisions on microservices, APIs, cloud infrastructure, and distributed systems, balancing performance, scalability, security, and cost. Drive predictable delivery - partner with Product and Design to plan effective releases, remove blockers, and balance shipping speed with quality. Champion engineering excellence - set standards for code quality, testing, and documentation, and track metrics on delivery, reliability, and developer productivity. Own infrastructure security and uptime - establish standards for cloud infrastructure, incident response, and disaster recovery, and ensure compliance with data protection regulations. Guide AI integration - define the AI-native product development approach and integrate LLMs and intelligent automation where they create meaningful value. Build the data platform function - lead the Data team to ensure well-governed data infrastructure that supports analytics and reporting. Build and scale the engineering organisation - define team structures, recruit and retain talent, and create career paths across technical and management tracks. Develop engineering leaders - coach Engineering Managers, Tech Leads, and senior engineers while embedding a culture of ownership and continuous learning. Act as a key cross-functional and executive partner - communicate technical trade-offs clearly to non-technical stakeholders and ensure Engineering stays aligned with company strategy.

Requirements:

10 years in software engineering, with significant experience leading engineering teams and complex technology products.

High-growth, complex environment experience - SaaS, HealthTech, FinTech, or similar, leading teams across multiple products, platforms, or technology domains.

Strong architectural background - designing and scaling production-grade systems, with solid understanding of backend, frontend, API, cloud, database, and distributed-system architecture.

Cloud & infrastructure expertise - strong experience with cloud platforms (preferably AWS), CI/CD, deployment, testing, observability, reliability, and security across the SDLC.

Large-scale technical ownership - experience managing technical products, technical debt, architecture evolution, and major engineering initiatives.

AI/ML experience is a strong plus - particularly AI-native product development.

Strong soft skills - analytical thinking, problem-solving, communication, and stakeholder management.

Bachelor's degree in Computer Science, Engineering, or related field; advanced degree is a plus.