Chief Technology Officer

Gloo
London
11 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist — Healthcare Analytics & Growth

Lead Site Reliability Engineer - DataOps

Lead Data Scientist

Lead Data Scientist

Applied AI and Machine Learning Scientist - Senior Associate

Artificial Intelligence Lead (18 month FTC)

Chief Technology Officer (CTO) – Fast-Growing HealthTech Business

Reporting to:CEO

About Us

We are a rapidly scaling HealthTech company dedicated to transforming healthcare through cutting-edge technology. With strong investor backing and a growing customer base, we are looking for a visionaryChief Technology Officer (CTO)to lead our technology strategy and execution.

The Role

As CTO, you will be responsible for shaping and executing our technology vision, driving product innovation, and ensuring our platform remains scalable, secure, and compliant with healthcare regulations. You will build and lead a high-performing engineering team while working closely with the executive team to align technology with business goals.

Key Responsibilities

  • Technology Strategy & Leadership:Define and implement the company’s technology vision and roadmap, ensuring alignment with business objectives.
  • Product Development:Oversee the architecture, development, and deployment of scalable, secure, and high-performance healthtech solutions.
  • Regulatory & Compliance:Ensure all technology solutions comply with healthcare regulations (e.g., HIPAA, GDPR, NHS Digital standards, ISO 27001).
  • Data & Security:Lead data security, governance, and privacy initiatives, ensuring best practices in handling patient and healthcare data.
  • Team Building & Leadership:Recruit, mentor, and scale a world-class engineering, DevOps, and product team to support rapid growth.
  • Innovation & Emerging Technologies:Drive innovation in AI, ML, telemedicine, and digital health solutions, identifying new opportunities for competitive advantage.
  • Partnerships & Stakeholder Management:Collaborate with internal teams, healthcare providers, payers, and external partners to enhance product offerings and market reach.
  • Infrastructure & Scalability:Ensure the reliability and performance of our platform as we scale, optimising cloud infrastructure and DevOps processes.

What We’re Looking For

  • Proven experience as aCTO, VP of Engineering, or Senior Technology Leaderin a HealthTech, MedTech, or regulated SaaS environment.
  • Strong technical background in software engineering, cloud infrastructure, and data security, with expertise in modern tech stacks.
  • Experience scaling technology teams in a fast-growth startup or scale-up.
  • Deep understanding ofhealthcare regulations and compliance(e.g., HIPAA, GDPR, NHS frameworks).
  • Strong leadership, team-building, and stakeholder management skills.
  • Track record of delivering innovative, user-centric digital health products.
  • Experience in AI, machine learning, or health data analytics is a plus.

Why Join Us?

  • Impact:Play a pivotal role in revolutionising healthcare technology.
  • Growth:Join a high-growth company with ambitious plans for expansion.
  • Equity & Ownership:Competitive salary with significant equity options.
  • Innovation:Work on cutting-edge technology in an industry that truly matters.

If you’re a visionary technology leader passionate about healthcare innovation, we’d love to hear from you.

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Jobs Careers

AI Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Changing career into artificial intelligence in your 30s, 40s or 50s is no longer unusual in the UK. It is happening quietly every day across fintech, healthcare, retail, manufacturing, government & professional services. But it is also surrounded by hype, fear & misinformation. This article is a realistic, UK-specific guide for career switchers who want the truth about AI jobs: what roles genuinely exist, what skills employers actually hire for, how long retraining really takes & whether age is a barrier (spoiler: not in the way people think). If you are considering a move into AI but want facts rather than Silicon Valley fantasy, this is for you.

Jobs

How to Write an AI Job Ad That Attracts the Right People

Artificial intelligence is now embedded across almost every sector of the UK economy. From fintech and healthcare to retail, defence and climate tech, organisations are competing for AI talent at an unprecedented pace. Yet despite the volume of AI job adverts online, many employers struggle to attract the right candidates. Roles are flooded with unsuitable applications, while highly capable AI professionals scroll past adverts that feel vague, inflated or disconnected from reality. In most cases, the issue isn’t a shortage of AI talent — it’s the quality of the job advert. Writing an effective AI job ad requires more care than traditional tech hiring. AI professionals are analytical, sceptical of hype and highly selective about where they apply. A poorly written advert doesn’t just fail to convert — it actively damages your credibility. This guide explains how to write an AI job ad that attracts the right people, filters out mismatches and positions your organisation as a serious employer in the AI space.

Education Jobs

Maths for AI Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are a software engineer, data scientist or analyst looking to move into AI or you are a UK undergraduate or postgraduate in computer science, maths, engineering or a related subject applying for AI roles, the maths can feel like the biggest barrier. Job descriptions say “strong maths” or “solid fundamentals” but rarely spell out what that means day to day. The good news is you do not need a full maths degree worth of theory to start applying. For most UK roles like Machine Learning Engineer, AI Engineer, Data Scientist, Applied Scientist, NLP Engineer or Computer Vision Engineer, the maths you actually use again & again is concentrated in a handful of topics: Linear algebra essentials Probability & statistics for uncertainty & evaluation Calculus essentials for gradients & backprop Optimisation basics for training & tuning A small amount of discrete maths for practical reasoning This guide turns vague requirements into a clear checklist, a 6-week learning plan & portfolio projects that prove you can translate maths into working code.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.