Engineering Manager

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. About the role We're looking for a hands-on Engineering Manager to lead our engineering team and drive the development, performance and reliability of Zofeur's live marketplace technology. This is an AI-first, hands-on leadership role that combines technical ownership with people management. You will personally use AI coding assistants and agents and lead their responsible adoption across the engineering workflow. Strong senior engineers with demonstrated leadership readiness are welcome to step into engineering management. A current Engineering Manager title is not a prerequisite. Key responsibilities Marketplace engineering and technical ownership Own and improve core marketplace systems (matching, dispatch, pickup ETA, pricing, fulfilment and supply–demand optimisation), building on relevant prior experience Identify and address production bottlenecks, performance issues and reliability challenges across real-time marketplace workflows Drive data-informed decisions that improve pickup times, fulfilment rates, cancellations, chauffeur utilisation and operational cost Take direct ownership of technical problem-solving: architecture discussions, code reviews, debugging and significant production changes Keep marketplace systems reliable, scalable and maintainable as business requirements evolve Engineering leadership and delivery Lead, mentor and develop the existing team, with clear ownership, accountability and high standards Own delivery end to end: planning, prioritisation, development, testing, deployment and post-release monitoring Improve team execution: stronger development practices, fewer bottlenecks, predictable high-quality releases Establish engineering standards, coding practices, testing strategies and documentation Work with Product, Operations and other stakeholders to prioritise and balance business impact, technical quality and timelines Build a culture of ownership, collaboration and continuous improvement Infrastructure reliability and technical operations Keep a strong focus on production reliability, monitoring, incident response and root-cause analysis Contribute to decisions on architecture, infrastructure, performance, security and data, taking ownership where the role and team require Identify technical debt and prioritise the improvements that most reduce operational risk or raise productivity Factor scalability, maintainability, security and cost efficiency into engineering decisions AI first engineering and continuous improvement Personally use AI coding assistants and agents in development, debugging and testing, validating generated output through engineering judgement, code review and testing Lead adoption of AI-enabled engineering workflows for implementation, code review, test generation and documentation, and coach the team on effective use Maintain accountability for code quality, security, privacy and production reliability, including safe handling of company and customer data when using AI tools Measure the impact of AI-enabled workflows on delivery cycle time, defect rates and engineering productivity, and refine practices based on results Evaluate AI tools and automation pragmatically, for measurable business value rather than experimentation Encourage continuous learning and effective engineering practices across the team Required Experience and Qualifications Strong software engineering experience delivering and operating production-grade technology, with evidence of leading projects, mentoring engineers or owning delivery. Experience working within a live, high-volume on-demand marketplace, preferably ride-hailing or mobility. Delivery or adjacent marketplace experience is relevant only where it includes substantive, direct ownership of comparable real-time allocation or marketplace decisions. Direct, hands-on ownership of at least one core marketplace system, such as matching, dispatch, pickup ETA prediction, dynamic pricing or supply-demand optimisation. General app development, maps integration or onboarding alone is not sufficient. Demonstrated personal contribution to designing, building, operating or improving production systems, supported by measurable operational or business outcomes. Recent, practical engineering involvement, including meaningful code contributions, implementation, debugging, code reviews or resolving complex production issues. Demonstrated, recent hands-on use of AI coding assistants or agents in actual development, debugging and testing, with examples of measurable delivery or quality improvements and how the output was validated. Strong understanding of real-time, transaction-heavy or event-driven systems and the technical challenges of marketplace operations. Demonstrated leadership capability and readiness to lead, mentor and develop engineers while remaining technically credible and involved in key architectural and engineering decisions. Experience owning end-to-end delivery, prioritising technical work and balancing business outcomes, engineering quality and delivery timelines. Sound technical judgement, with experience improving system reliability, scalability, maintainability and operational efficiency in a fast-moving environment. Excellent communication and stakeholder management skills, with the ability to collaborate effectively across Engineering, Product, Operations and other business functions. Success will be measured by your ability to Improve marketplace performance through meaningful technical changes Deliver measurable gains in fulfilment, pickup times, cancellations, utilisation or operational efficiency within your area of ownership Strengthen engineering execution, accountability and delivery predictability Demonstrate measurable improvements in delivery cycle time, quality or productivity through AI-enabled engineering workflows, while maintaining code review, security, privacy and production reliability Keep production systems reliable, scalable and maintainable Develop the engineering team while retaining strong technical ownership Translate business priorities into effective engineering outcomes Show more Show less