AI and Business Unit Leadership

Accountabilities:: Partner with the CEO to define and execute the overall technology strategy while taking ownership of a business unit, including its priorities, execution, performance, and commercial outcomes. Align technology investments and development priorities with customer needs, market opportunities, and broader business objectives, working closely with Product and Commercial teams. Drive the practical adoption of artificial intelligence, large language models (LLMs), and automation across products and engineering workflows, identifying opportunities to improve efficiency, product capabilities, and customer value. Establish clear success metrics for AI initiatives and oversee their implementation, ensuring that solutions deliver measurable improvements in quality, reliability, cost efficiency, and business performance. Lead and develop a multidisciplinary technology organization through Engineering Managers, Technical Leads, Infrastructure Leaders, and Data Science teams, fostering accountability, autonomy, and continuous improvement. Provide strategic direction and decision-making ownership to technical leaders while strengthening organizational capabilities, developing talent, and maintaining high standards of execution. Oversee the evolution of high-throughput, real-time technology infrastructure to support business growth, ensuring scalability, resilience, security, and operational reliability. Balance rapid innovation and experimentation with robust engineering practices, ensuring that technology platforms consistently meet the expectations of partners and customers. Challenge architectural and technical decisions, ensuring alignment between engineering execution, product strategy, and long-term business requirements. Maintain close collaboration with executive leadership and cross-functional stakeholders to translate strategic ambitions into actionable plans and measurable results. Requirements: Strong professional background in software engineering, technology architecture, or a related technical discipline, with the ability to engage confidently in complex engineering discussions and challenge senior technical decisions. Proven experience leading substantial technology or engineering organizations, particularly through Engineering Managers, Technical Leads, and other senior leaders. Demonstrated success in developing leadership teams, establishing clear accountability structures, and creating a culture of autonomy, ownership, and continuous improvement. Experience in technology strategy and business leadership, ideally with direct responsibility for a business unit, product area, or comparable commercial operation. Strong commercial awareness and the ability to connect technical decisions with customer requirements, investment priorities, revenue opportunities, and business performance. Hands-on experience using AI technologies, including LLMs, AI-powered development tools, and automation workflows, with a clear understanding of their practical applications and limitations. Proven ability to move AI initiatives from experimentation into production, evaluating their impact on quality, reliability, scalability, cost, and customer value. Experience managing complex, high-performance technology platforms, ideally involving real-time systems, high-throughput infrastructure, or data-intensive applications. Strong understanding of infrastructure scalability, system resilience, cybersecurity, and operational excellence. Excellent strategic thinking, communication, and stakeholder management skills, with the ability to work effectively with executive leadership, technical teams, product stakeholders, and commercial functions. A proactive, entrepreneurial mindset, combining technical credibility with business ownership and the ability to make sound decisions in a fast-moving environment. Benefits: Direct CEO partnership: Work closely with a technical founder, contributing to strategic decisions and helping translate ambitious technology objectives into business results. Advanced AI infrastructure: Access to a dedicated NVIDIA B300 GPU cluster, providing significant resources to develop and deploy innovative AI solutions. Real-world AI impact: Opportunity to apply AI, LLMs, and automation to data-rich products and engineering workflows at scale. Strategic ownership: Take responsibility for a business unit while shaping the wider technology strategy and organizational direction. Leadership opportunities: Build, develop, and empower a talented international team of engineering and technology professionals. Innovation-driven environment: Join a data-focused technology business operating at the intersection of AI, analytics, and real-time digital experiences. Professional impact: Influence product development, technical architecture, operational excellence, and long-term commercial growth. Remote working: Opportunity to work remotely within an international environment.