Chief Technology Officer

Chief Technology Officer: Hands-on, AI-native technology leadership for Zofeur's next stage of scale Reports to: Founder & CEO Scope: Engineering, architecture, mobile, QA, DevOps, infrastructure, cybersecurity, data engineering and AI engineering The Opportunity Build the technology organisation behind a high-volume, real-time mobility platform. This is a company-level leadership role for a technically deep operator who can strengthen an existing platform, upgrade a distributed team and make AI a practical advantage across engineering and mobility intelligence. About Zofeur Zofeur is a fast-growing mobility technology platform built around delegated mobility for car owners. The platform powers on-demand chauffeur services, scheduled and subscription-based mobility, enterprise driver logistics and related operational services across multiple markets. Its technology environment includes customer and chauffeur mobile applications, real-time dispatch and location systems, payments, subscriptions, operational control systems, enterprise dashboards, APIs, analytics and cloud infrastructure. Zofeur is now building its next stage of internal technology leadership as it scales across the GCC. The role Zofeur is seeking a hands-on, AI-native Chief Technology Officer to take end-to-end ownership of technology strategy, engineering execution and organisational capability. The CTO will inherit a live platform and an established distributed engineering team. The immediate mandate is to strengthen that team, internalise critical capabilities, improve delivery speed and quality, reduce key-person dependency and build a high-performing engineering organisation. This is not a purely strategic or managerial position. The CTO must be technically credible enough to engage directly with architecture, code quality, infrastructure and production incidents while building the leadership structure required for scale. What you will own Technology strategy and architecture • Own Zofeur's technical vision, architecture and engineering roadmap. • Ensure the platform can support increasing transaction volumes, geographic expansion and new product lines. • Review the current cloud, backend, mobile, data and integration architecture and establish clear technical standards. • Prioritise technical debt according to customer, operational and commercial impact. • Make pragmatic build-versus-buy, modernisation and platform investment decisions. • Improve systems incrementally while replacing components where evidence clearly justifies it. Engineering organisation • Assess the existing engineering organisation and develop a clear capability and succession plan. • Build an internal technology organisation while managing a controlled hybrid delivery model. • Recruit, coach and retain high-quality engineering leaders and individual contributors. • Establish clear ownership across backend, mobile, QA, infrastructure, security, data and AI engineering. • Eliminate critical individual dependencies and create an accountable, transparent engineering culture. Delivery, reliability and quality • Improve engineering velocity without compromising platform stability. • Establish measurable standards for release frequency, lead time, defect rate, availability and incident recovery. • Strengthen QA automation across critical customer, chauffeur, payment, subscription, B2B and operational workflows. • Implement effective code review, testing, deployment, rollback, observability and incident-response practices. • Improve technical documentation and engineer onboarding. AI-first engineering and mobility intelligence • Establish AI-native development practices across coding, testing, review, documentation, debugging and internal tooling. • Select and govern AI development tools with appropriate security, privacy and quality controls. • Build capability in data engineering, AI engineering and MLOps. • Partner with Product and Operations to convert high-value AI opportunities into reliable production systems. • Lead initial priorities including automated software engineering and QA, ETA and demand forecasting, and pricing and supply planning. Cloud, security and governance • Own AWS and GCP architecture, availability, security and cost management. • Establish strong identity, access, secrets and production-control policies. • Ensure Zofeur maintains complete control over source code, infrastructure and critical third-party systems. • Strengthen cybersecurity, privacy, business continuity and disaster recovery. • Prepare the technology organisation for enterprise diligence, regional expansion and future compliance requirements. Executive leadership • Act as a strategic partner to the Founder and CEO and challenge priorities constructively. • Translate company objectives into credible technology plans, budgets, trade-offs and timelines. • Represent technology with the board, investors, strategic partners and enterprise customers. • Build a culture of accountability, urgency, transparency and continuous improvement. What success looks like • Technology ownership has moved from founder-led decision-making to a clear, CTO-led operating model. • Zofeur has a strong internal engineering core supported by carefully governed external capacity. • Critical systems and responsibilities have documented owners and no material single-person dependencies. • Release speed, reliability, defect rates and incident recovery are measured and materially improving. • AI is embedded in everyday engineering delivery and selected mobility-intelligence use cases are operating in production. • The technology organisation can support GCC expansion without proportionally increasing complexity or headcount. Candidate profile The successful candidate will likely bring: • Significant software engineering and technology leadership experience, typically 12 or more years, with evidence valued above tenure. • Experience leading and scaling multidisciplinary engineering organisations. • Strong architecture capability across cloud, backend, mobile, data and APIs. • Experience with high-volume transactional, marketplace, logistics, mobility, delivery, fintech or consumer platforms. • Direct exposure to real-time systems, location data, payments or operational platforms. • Experience managing distributed internal teams and outsourced engineering partners. • A record of recruiting, assessing and upgrading engineering talent. • Practical experience implementing AI-assisted software development and production AI systems. • Strong knowledge of QA automation, DevOps, observability, security and incident management. • Commercial judgement and the ability to connect technical decisions to customer and business outcomes. • The confidence and communication skills to work directly with founders and boards. • Experience with PHP/Laravel, Swift, Kotlin, AWS, GCP, Redshift or mobility technology is advantageous bu

Significant software engineering and technology leadership experience, typically 12 or more years. Experience leading and scaling multidisciplinary engineering organisations. Strong architecture capability across cloud, backend, mobile, data and APIs. Experience with high-volume transactional, marketplace, logistics, mobility, delivery, fintech or consumer platforms. Direct exposure to real-time systems, location data, payments or operational platforms. Experience managing distributed internal teams and outsourced engineering partners. A record of recruiting, assessing and upgrading engineering talent. Practical experience implementing AI-assisted software development and production AI systems. Strong knowledge of QA automation, DevOps, observability, security and incident management. Commercial judgement and the ability to connect technical decisions to customer and business outcomes. The confidence and communication skills to work directly with founders and boards.

Own technology strategy, architecture and engineering roadmap. Ensure the platform can support increasing transaction volumes, geographic expansion and new product lines. Review current cloud, backend, mobile, data and integration architecture and establish technical standards. Prioritise technical debt. Make build-versus-buy decisions. Improve systems incrementally while replacing components where justified. Assess and develop internal engineering capability and succession plans. Build an internal technology organisation with a hybrid delivery model. Recruit, coach and retain engineering leaders and contributors. Establish clear ownership across backend, mobile, QA, infrastructure, security, data and AI engineering. Eliminate dependencies and foster an accountable engineering culture. Improve engineering velocity with stability. Establish standards for release frequency, lead time, defect rate, availability and incident recovery. Strengthen QA automation across key workflows. Implement code review, testing, deployment, rollback, observability and incident-response practices. Improve documentation and onboarding. Establish AI-native development practices and govern AI tools with security, privacy and quality controls. Build capability in data engineering, AI engineering and MLOps. Partner with Product and Operations to turn AI opportunities into production systems. Lead priorities including automated software engineering, QA, ETA and demand forecasting, pricing and supply planning. Own AWS and GCP architecture, availability, security and cost management. Establish identity, access, secrets, and production-control policies. Ensure control over source code, infrastructure and critical third-party systems. Strengthen cybersecurity, privacy, business continuity and disaster recovery. Prepare for enterprise diligence, regional expansion and compliance. Act as strategic partner to Founder/CEO, translate objectives into technology plans, budgets and timelines. Represent technology with board, investors and enterprise customers. Build a culture of accountability, urgency, transparency and continuous improvement.