Head of Engineering

Gloo
London
1 year ago
Applications closed

Related Jobs

View all jobs

Data Engineering Manager

Data Engineering Manager

Head of Data Engineering — Scale Data Platforms & Teams

Head of Data Engineering (Manchester/Hybrid, UK)

Head of Data Engineering (Manchester/Hybrid, UK)

Head of Data Engineering

My client is a pioneering AI company dedicated to building a powerful AI-driven search and discovery product that transforms how users interact with information. Their mission is to leverage the latest advancements in artificial intelligence to create seamless, intelligent experiences that drive value for our users. We are looking for a talented and visionary Head of Engineering to lead our engineering efforts, drive technical strategy, and scale our product to the next level.

Position Overview:

The Head of Engineering will oversee our engineering teams, responsible for the end-to-end development of our AI-powered search and discovery product. This role combines leadership and technical expertise, and the ideal candidate is someone with deep experience in artificial intelligence, machine learning, and search technologies. You’ll work closely with cross-functional teams, including Product, Data Science, and Design, to ensure our technology solutions meet both current and future needs.

Key Responsibilities

  • Leadership & Strategy
  • Define and drive the technical strategy for our AI-powered search and discovery product, ensuring alignment with business objectives.
  • Provide strong leadership and mentorship to a high-performing engineering team, fostering a collaborative and innovative culture.
  • Build and scale the engineering team through recruiting, hiring, and developing world-class engineering talent.
  • Collaborate closely with Product, Data Science, and Design teams to align engineering initiatives with product goals and user needs.
  • Technical Oversight
  • Oversee the design, architecture, and implementation of our AI search platform, focusing on scalability, reliability, and performance.
  • Lead the development of core search and discovery technologies, such as NLP, large language models, recommendation systems, and personalized search algorithms.
  • Ensure that best practices in software engineering, security, and quality assurance are integrated into every phase of the development lifecycle.
  • Drive continuous improvement initiatives, promoting an agile and adaptable engineering culture.
  • Innovation & Product Development
  • Work with Product to set a roadmap for the development and release of new features and capabilities.
  • Guide the research and development of cutting-edge AI techniques that differentiate our product and enhance user experiences.
  • Lead technical due diligence for partnerships and evaluate third-party solutions to augment our AI capabilities.
  • Identify opportunities to leverage emerging technologies, such as GPT-based models, vector databases, and knowledge graphs, to improve search accuracy and personalization.
  • Operational Excellence
  • Ensure high availability and reliability of all systems, with a focus on monitoring, alerting, and incident management.
  • Oversee budget and resource allocation within the engineering team, optimizing for maximum productivity and ROI.
  • Foster an inclusive and performance-driven environment, with a focus on transparency, accountability, and clear goal-setting.

Qualifications

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
  • 10+ years of experience in software engineering, with at least 3 years in a leadership role.
  • Proven track record of managing engineering teams, ideally within AI, machine learning, or search-focused technology companies.
  • Hands-on experience with AI/ML technologies, including NLP, deep learning, recommendation engines, and large-scale data processing.
  • Familiarity with modern AI frameworks (e.g., TensorFlow, PyTorch) and cloud-based architectures (e.g., AWS, GCP).
  • Expertise in building scalable, high-performance applications and familiarity with microservices, distributed systems, and DevOps best practices.
  • Strong project management skills and the ability to communicate complex technical concepts effectively.
  • Passion for innovation in AI search and a user-first approach to product development.

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.

Careers Jobs

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

Are you considering a career change into machine learning in your 30s, 40s or 50s? You’re not alone. In the UK, organisations across industries such as finance, healthcare, retail, government & technology are investing in machine learning to improve decisions, automate processes & unlock new insights. But with all the hype, it can be hard to tell which roles are real job opportunities and which are just buzzwords. This article gives you a practical, UK-focused reality check: which machine learning roles truly exist, what skills employers really hire for, how long retraining realistically takes, how to position your experience and whether age matters in your favour or not. Whether you come from analytics, engineering, operations, research, compliance or business strategy, there is a credible route into machine learning if you approach it strategically.

Jobs

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

Education Jobs

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

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.

🍪 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.