Chief Technology Officer in London

Location: United Kingdom / hybrid, with a globally distributed team

Reporting to: Founder & CEO

Leadership team: Executive Leadership Team

The opportunity

A technology company is entering its next phase of growth. We are looking for a hands-on, commercially minded CTO to shape company strategy and lead technology, engineering and data science. This is not a purely managerial role. You will move comfortably between architecture, AI and product discussions, executive decision-making, and conversations with customers and investors. You will combine strategic perspective with the technical depth to challenge assumptions and get into the detail when it matters.

The mission

• Turn technology and data science into a clear competitive advantage.
• Build and execute a technology strategy that supports growth.
• Scale engineering and data science while protecting speed, quality and ambition.
• Make clear build, buy, simplify and stop decisions.
• Improve the path from idea to production and customer value.
• Develop an outstanding technical leadership team and high-performing culture.
• Represent the company's technology and AI story to customers, partners and investors.

What you'll actually do

1. Set the technology strategy - Own a pragmatic multi-year strategy covering product and platform architecture, AI and data science, cloud infrastructure, security, technical operations, developer productivity and investment priorities. Translate long-term direction into clear near-term decisions.
2. Remain technically engaged - Stay close enough to the technology to review critical designs, challenge architecture, explore ML approaches, diagnose scalability or performance issues and help Product decide whether something should be built. Lead through leverage without becoming the decision-making bottleneck.
3. Build the organisation - Develop strong engineering and data science leaders, establish clear ownership, hire excellent talent and create an effective structure for the company's stage. Build a culture of curiosity, pace, accountability, autonomy and high standards.
4. Improve velocity and quality - Strengthen architecture, development practices, CI/CD, testing, automation, observability, reliability, security, incident management and technical debt management. Use practical measures such as cycle time, deployment frequency, uptime, defect rates, infrastructure efficiency and developer productivity to drive improvement.
5. Advance AI and data capabilities - Guide the evolution of machine learning, advanced data modelling, personalisation, data products, real-time processing, experimentation and model deployment. Help move research into production and focus investment on genuine differentiation and commercial value.
6. Connect technology to commercial outcomes - Partner closely with Product, Commercial, Customer Success, Marketing and Operations. Align the roadmap to customer needs, revenue, retention and strategic differentiation. Identify what to productise, what should become a platform capability and which constraints could limit growth.
7. Act as an external technology leader - Explain complex technology clearly to technical audiences, executives, customers and investors. Support enterprise sales, strategic partnerships and future fundraising by articulating the value, scalability and defensibility of the technology.
8. Own economics and risk - Manage technology budgets, headcount, infrastructure costs, suppliers, capacity planning, security, compliance, resilience and business continuity. Connect technical choices to cost, risk and commercial return.

What success looks like

• A clear technology strategy aligned with company priorities.
• A scalable, secure and appropriately governed architecture.
• Faster, more predictable delivery and stronger engineering quality.
• Better reliability, developer experience and infrastructure efficiency.
• Reduced technical debt and clearer build, buy and sunset decisions.
• Faster movement from research to production and customer value.
• Strong technical leaders with clear ownership and increasing autonomy.
• Visible contribution from technology to growth, retention and differentiation.
• Transparent technology investment tied to business priorities.

The technology

The environment includes technologies such as Scala, Python, Kubernetes, Spark, Hive, AWS, Docker, Terraform, Vault, TypeScript, React, Go and Rust. You do not need experience with every technology. Technical depth, architectural judgement and the ability to learn quickly matter more than matching the stack exactly.

What we're looking for

• Strong engineering credibility and the ability to go deep technically.
• Senior technology leadership in a complex, data-intensive or enterprise SaaS environment.
• Deep knowledge of cloud architecture, distributed systems and operational excellence.
• Significant exposure to data science, AI or ML at scale.
• Experience governing architecture across data, ML, platform and customer-facing products.
• A track record of scaling engineering organisations and developing leaders.
• Strong product instincts and a focus on solving customer problems.
• Commercial judgement and experience linking technology investment to business outcomes.
• Confidence with customers, investors and other senior stakeholders.
• Experience managing meaningful budgets, vendors and resource allocation.
• The ability to make difficult trade-offs and communicate them clearly.

Leadership style

The strongest candidate will be a builder, operator and strategist who:

• Is hands-on without needing to be the hero.
• Thinks strategically and converts strategy into execution.
• Holds strong opinions but changes course when evidence changes.
• Raises standards while building trust, autonomy and psychological safety.
• Creates clarity and enables teams to make good decisions independently.
• Leads with warmth, intellectual rigour and low ego.

A particularly strong fit

You may be especially well suited if you have worked in a high-growth SaaS, data or AI.