Cloud Architect and Engineering Team Lead

CUBE
London
5 months ago
Applications closed

Related Jobs

View all jobs

Machine Learning and AI Engineering Lead

Data Security Engineer

MLOps Field Engineer

Senior Data Science Developer

Senior Data Science Developer

Data Engineer

 


Role: Cloud Architect and Engineering Team Lead. 

Location: London, with the expectations of one day a week in the office. 

Recently listed as a "RegTech Top Performer" in Market Fintech's RegTech Supplier Performance Report, CUBE is pioneering the development of machine automated compliance. 

We are a global RegTech business defining and implementing the gold standard of regulatory intelligence and change for the financial services industry. We deliver our services through a SaaS platform, powered by an innovative combination of AI and proprietary data ontology, to simplify the complex and everchanging world of compliance for our clients. 

At CUBE, we are creating the future and are a company rooted in strong values, team spirit and commitment to our customers and wider communities. We serve some of the largest financial institutions globally and are expanding our footprint very fast. As we do so, we are keen for new talent to join us and realize their full potential to grow into leadership positions within the business.   

Role mission:  

The Cloud Architecture and Engineering Team Leader will be responsible for overseeing and contributing to the design, implementation, and maintenance of comprehensive Azure solutions. This role requires a balance of strategic architecture planning and hands-on engineering work. The ideal candidate will lead a local team in the UK while collaborating with global peers to deliver secure, scalable, and optimized cloud solutions. 

Responsibilities: 

  •  Lead the UK cloud team, combining architectural oversight with hands-on engineering work to develop and deploy Azure-based solutions.
  • Collaborate with global teams to create and implement comprehensive cloud strategies aligned with business objectives.
  • Design and build scalable, secure, and high-performance Azure infrastructure and applications.
  • Establish and enforce best practices in cloud architecture, automation, and continuous integration/continuous deployment (CI/CD).
  • Serve as the go-to expert for cloud technologies and provide practical, technical guidance on infrastructure as code (IaC), containerization, and cloud-native practices.
  • Oversee cloud cost management and optimization, ensuring efficient use of resources.
  • Maintain compliance with security and industry regulations for cloud environments.
  • Mentor and develop team members, fostering an environment of innovation and continuous learning.
  • Proactively engage in troubleshooting complex issues and delivering robust solutions.

Whatwe’re looking for: 

  • Demonstrated experience in a combined architecture and engineering leadership role, preferably with a focus on Microsoft Azure.
  • Strong technical expertise in Azure services, IaaS, PaaS, and SaaS solutions.
  • Hands-on experience with infrastructure as code tools (e.g., ARM templates, Bicep or preferably Terraform) and CI/CD pipelines.
  • Deep understanding of cloud security best practices, resilience and identity/access management.
  • Proven problem-solving skills with the ability to manage and guide a team effectively.
  • Excellent communication skills to collaborate with stakeholders at all levels.

Preferred Skills:

  • Experience working with multi-cloud or hybrid cloud environments.
  • Proficiency in containerization tools such as Docker and Kubernetes.
  • Microsoft Azure certifications (e.g., Azure Solutions Architect Expert, Azure DevOps Engineer Expert).
  • Data engineering or MLOps knowledge a plus
  • Knowledge of Agile methodologies and experience in dynamic environments.
  • Bachelor's degree in Computer Science, Engineering, or a related field (or equivalent experience).

Our Products:

RegPlatformis a technology platform that streamlines regulatory change management. It provides firms with a one-stop, continuously maintained inventory of global regulations, with effortless horizon scanning, integration capabilities and workflow management. RegPlatform combines industry leading AI technology with expert validated insights to simplify the complexities of multi-jurisdictional regulatory content.

RegBrainallows customers to apply CUBE's AI models directly to their own content, enabling faster release and feedback cycles. Our flagship AI services will be included, spanning structural detection, classification, entity extraction, summarisation, and recommendations. Available to customers and partners as APIs and via a UI.

Why Us?   

 Globally, we are one of a kind! 

CUBE are a well-established market leader within Regtech (we were around before Regtech was even a thing!), and our category-defining product is used by leading financial institutions around the world (including Revolut, Citi, and HSBC).

Growth & progression

Last year we grew by more than 50% and our growth journey is just getting started! We are a dynamic, fast-paced workforce that is always seeking ways to accelerate our people, processes, services and products. We hire ambitious people that want to make a difference, share their ideas, “make it happen” and find better, smarter ways of working. Our future is shaped by our employees, so if you’re someone looking for an opportunity to make a real impact, and progress your career alongside the business, it couldn’t be a better time to join us!

Internationally collaborative culture

With more than 400 CUBERs across 11 locations in Europe, the Americas and APAC, collaboration is key to our success. We are a diverse workforce united by a shared desire to reshape the world of regulatory compliance and make an impact. We champion sharing knowledge with colleagues from all over the world, in order to deliver the best results.

 Innovative breakthrough technology

CUBE is an innovator. We pioneered the use of AI in the field of regulatory change and our state-of-the-art, cutting edge technology is helping financial services firms from all over the world, solve complex compliance challenges. You will work alongside some of the brightest minds in AI research and engineering in developing impactful solutions that will reshape the world of regulatory compliance.

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Portfolio Projects That Get You Hired for AI Jobs (With Real GitHub Examples)

In the fast-evolving world of artificial intelligence (AI), an impressive portfolio of projects can act as your passport to landing a sought-after role. Even if you’ve aced interviews in the past, employers in AI and machine learning (ML) are increasingly asking candidates to demonstrate hands-on experience through the projects they’ve built and shared online. This is because practical ability often speaks volumes about your suitability for a role—far more than any exam or certification alone could. In this article, we’ll explore how to build an outstanding AI portfolio that catches the eye of recruiters and hiring managers, including: Why an AI portfolio is crucial for job seekers. How to choose AI projects that align with your target roles. Specific project ideas and real GitHub examples to help you stand out. Best practices for showcasing your work, from writing clear READMEs to using Jupyter notebooks effectively. Tips on structuring your GitHub so that employers can instantly see your value. Moreover, we’ll discuss how you can use your portfolio to connect with top employers in AI, with a handy link to our CV-upload page on Artificial Intelligence Jobs for when you’re ready to apply. By the end, you’ll have a clear roadmap to building a portfolio that will help secure interviews—and the AI job—of your dreams.

AI Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

In today's competitive AI job market, nailing a technical interview can be the difference between landing your dream role and getting lost in the crowd. Whether you're looking to break into machine learning, deep learning, NLP (Natural Language Processing), or data science, your problem-solving skills and system design expertise are certain to be put to the test. AI‑related job interviews typically involve a range of coding challenges, algorithmic puzzles, and system design questions. You’ll often be asked to delve into the principles of machine learning pipelines, discuss how to optimise large-scale systems, and demonstrate your coding proficiency in languages like Python, C++, or Java. Adequate preparation not only boosts your confidence but also reduces the likelihood of fumbling through unfamiliar territory. If you’re actively seeking positions at major tech companies or innovative AI start-ups, then check out www.artificialintelligencejobs.co.uk for some of the latest vacancies in the UK. Meanwhile, this blog post will guide you through 30 real coding & system-design questions you’re likely to encounter during your AI job interview. This list is designed to help you practise, anticipate typical question patterns, and stay ahead of the competition. By reading through each question and thinking about the possible approaches, you’ll sharpen your problem-solving skills, time management, and critical thinking. Each question covers fundamental concepts that employers regularly test, ensuring you’re well-equipped for success. Let’s dive right in.

Negotiating Your AI Job Offer: Equity, Bonuses & Perks Explained

Artificial intelligence (AI) has proven itself to be one of the most transformative forces in today’s business world. From smart chatbots in customer service to predictive analytics in finance, AI technologies are reshaping how organisations operate and innovate. As the demand for AI professionals grows, so does the complexity of compensation packages. If you’re a mid‑senior AI professional, you’ve likely seen job offers that include far more than just a base salary—think equity, bonuses, and a range of perks designed to entice you into joining or staying with a company. For many, the focus remains squarely on salary. While that’s understandable—after all, your monthly take‑home pay is what covers day-to-day expenses—limiting your negotiations to salary alone can leave considerable value on the table. From stock options in ambitious startups to sign‑on bonuses that ‘buy you out’ of your current contract, modern AI job offers often include elements that can significantly boost your long-term wealth and job satisfaction. This article aims to shed light on the full scope of AI compensation—specifically focusing on how equity, bonuses, and perks can enhance (or sometimes detract from) the overall value of your package. We’ll delve into how these elements work in practice, what to watch out for, and how to navigate the negotiation process effectively. Our goal is to provide mid‑senior AI professionals with the insights and tools to land a holistic compensation deal that accurately reflects their technical expertise, leadership potential, and strategic importance in this fast-moving field. Whether you’re eyeing a leadership role in machine learning at an established tech giant, or you’re considering a pioneering position at a disruptive AI startup, the knowledge in this guide will help you weigh the merits of base salary alongside the potential riches—and risks—of equity, bonuses, and other benefits. By the end, you’ll have a clearer sense of how to align your compensation with both your immediate lifestyle needs and long-term career aspirations.