Gloo
Chief Technology Officer
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Chief Technology Officer
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
Over the next 24-36 months, you will:
- 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
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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. -
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. -
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.
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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. -
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. -
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. -
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. -
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
Within 12-24 months, we expect to see:
- 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.
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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
You will likely bring:
- 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 company; scaled an engineering organisation without losing culture or velocity; helped turn R&D into commercial products; worked with enterprise customers.
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