Chief Technology Officer

About the company

We’re working with an AI company developing personal intelligence: systems that understand context, interact naturally with people and help them complete tasks across their digital lives.

The company’s ambition spans foundation models, agentic software and purpose-built hardware. Delivering that vision requires close collaboration between research, engineering and product, with equal attention to model capability and the quality of the everyday experience.

About the role

We’re seeking a Chief Technology Officer to define the technical strategy and build the engineering organisation needed to turn ambitious AI capabilities into dependable products.

You’ll lead decisions across application architecture, agent execution, model integration, infrastructure and the interfaces between software and hardware. A central challenge will be making systems that can reason and act behave predictably in real environments, where context is incomplete, external services change and failures have practical consequences for users.

You’ll recruit and develop technical leaders while remaining closely involved in architectural decisions, difficult engineering problems and product readiness. You’ll partner with research leadership to translate advances into production capabilities and establish a clear path from experimentation to deployment.

What you’ll do

Set the technical strategy

• Define the architecture and engineering roadmap supporting the company’s product vision.
• Establish clear boundaries and interfaces across models, agent systems, applications, infrastructure and devices.
• Make informed build-versus-buy decisions, identifying where proprietary technology creates lasting value.
• Balance rapid development with reliability, maintainability and operating cost.
• Set technical milestones and identify dependencies that could limit delivery.

Build dependable agent systems

• Guide the development of systems that translate user intent into actions across applications and services.
• Establish approaches to tool execution, state management, permissions, retries and recovery.
• Design for interruptions, incomplete information and changes in external interfaces.
• Define where systems should act independently, request clarification or seek user confirmation.
• Create evaluation methods that measure task completion, failure recovery and user experience.

Connect research with production engineering

• Partner with research leaders on model integration, serving requirements and deployment constraints.
• Build a repeatable process for evaluating new model capabilities before introducing them into products.
• Ensure researchers and engineers can diagnose whether failures originate in models, orchestration or application behaviour.
• Develop feedback loops that turn production experience into useful research and engineering priorities.
• Plan infrastructure investment around measurable requirements for latency, throughput and quality.

Own platform reliability and performance

• Lead the development of infrastructure for model serving, application services and agent workloads.
• Establish observability across requests, inference, tool calls and task execution.
• Set service objectives and engineering practices for incident response and recovery.
• Improve responsiveness and cost efficiency as usage grows.
• Ensure releases can be evaluated, monitored and rolled back effectively.

Design for personal context and trust

• Guide the architecture for persistent context, personalisation and memory.
• Establish controls for identity, access, sensitive information and external integrations.
• Make user permissions and data boundaries explicit throughout the system.
• Ensure users can understand and manage information retained about them.
• Incorporate security and privacy into technical design and release decisions.

Coordinate software and hardware development

• Partner with hardware and embedded engineering leaders on device-to-cloud architecture.
• Assess trade-offs involving on-device processing, connectivity, power consumption and cloud inference.
• Align software capabilities with device constraints and release schedules.
• Maintain a coherent experience across physical interfaces and supporting applications.

Build the engineering organisation

• Recruit and develop leaders across the agreed engineering remit.
• Define ownership, decision-making responsibilities and interfaces between teams.
• Establish effective architecture reviews, planning and delivery practices.
• Maintain a high standard for technical judgement, implementation quality and operational accountability.
• Communicate progress, risks and investment requirements clearly to executive leadership.

What we’re looking for

• Significant technical leadership experience building and operating complex software platforms.
• A track record of scaling engineering organisations while remaining credible in detailed architectural discussions.
• Experience bringing AI or machine learning capabilities into production products.
• Strong understanding of distributed systems, model serving and performance-sensitive applications.
• Evidence of delivering products where responsiveness, reliability and user experience are critical.
• The ability to lead across research, infrastructure and product engineering.
• Strong judgement about technical risk, sequencing and resource allocation.
• Experience hiring and developing senior engineers and engineering leaders.
• Clear communication and the ability to translate technical constraints into business decisions.
• Comfort operating in an ambitious environment with evolving requirements.

Particularly relevant experience

• Agentic systems, computer-use agents or tool-using AI applications.
• Multimodal interfaces involving speech, vision or persistent context.
• Consumer products with demanding latency and availability requirements.
• Personalisation or memory systems handling sensitive user information.
• Device-to-cloud platforms, embedded software or integrated hardware products.
• Leading engineering alongside an internal foundation-model research team.

What success looks like

• A clear technical architecture that connects research capabilities with usable products.
• Agent systems that complete tasks reliably and recover effectively when conditions change.
• Measurable improvements in responsiveness, availability and operating efficiency.
• An engineering organisation with strong leaders, clear ownership and consistent delivery.
• Security, privacy and user control embedded in the product’s foundations.
• Technical investment aligned with the capabilities that matter most to users.