Cloud Infrastructure Engineer - AI Startup, Remote, £85K

London
2 months ago
Applications closed

Related Jobs

View all jobs

Senior Cloud Engineer (AWS)

Azure AI Engineer

Lead Machine Learning Engineer

Data Engineer

DevOps Engineer

Technical Lead Software Engineer

About Us:
Join a pioneering tech company at the forefront of AI and machine learning innovation. Our team comprises experts from top-tier institutions and industry leaders, all dedicated to developing cutting-edge technology. We are backed by prominent investors and offer a collaborative environment where your contributions will have a significant impact on the future of AI applications.

Responsibilities:

  • Collaborate with founders and engineering leaders to determine optimal cloud solutions.
  • Architect and manage cloud infrastructure on AWS, Azure, and GCP.
  • Ensure efficient data storage, processing, and security.
  • Identify and resolve issues in cloud infrastructure and deployments.
  • Automate provisioning, configuration, and deployment using IaC tools like Terraform and Ansible.
  • Develop robust backend services and APIs using Python frameworks (Django, Flask, FastAPI).
  • Design and implement CI/CD pipelines with tools like Gitlab CI/CD.
  • Focus on cloud security, software-defined networks, and compliance.

    Requirements:
  • Bachelor's or Master's degree from a well-known university, preferably Oxbridge, a member of the Russell Group, or Ivy League, in Computer Science, Engineering, IT, Mathematics, or a related field.
  • 5+ years of experience in cloud engineering, infrastructure engineering, or backend development.
  • Proficiency with cloud-native applications and microservice architecture.
  • Profound knowledge and hands-on experience in Large Language Model or AI/ML.
  • Hands-on experience with IaC tools (Terraform, CloudFormation) and Kubernetes.
  • Experience with large-scale automated cloud services in AWS or other public clouds.
  • Knowledge of network infrastructure in cloud environments, including DNS, BGP, VPC Peering, and more.
  • Experience with container orchestration platforms like ECS or Kubernetes and service mesh (Istio, Envoy).
  • Familiarity with edge/CDN networking products (Cloudflare, Cloudfront, Fastly).
  • Proven ability to influence technical decisions and execution within an organisation.

    Interested parties, please submit your application with an updated CV. Alternatively, please reach out to Brian Law at for a confidential chat.

    Hays Specialist Recruitment Limited acts as an employment agency for permanent recruitment and employment business for the supply of temporary workers. By applying for this job you accept the T&C's, Privacy Policy and Disclaimers which can be found at (url removed)

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.

10 Ways AI Pros Stay Inspired: Boost Creativity with Side Projects, Hackathons & More

In the rapidly evolving world of Artificial Intelligence (AI), creativity and innovation are critical. AI professionals—whether data scientists, machine learning engineers, or research scientists—must constantly rejuvenate their thinking to solve complex challenges. But how exactly do these experts stay energised and creative in their work? The answer often lies in a combination of strategic habits, side projects, hackathons, Kaggle competitions, reading the latest research, and consciously stepping out of comfort zones. This article will explore why these activities are so valuable, as well as provide actionable tips for anyone looking to spark new ideas and enrich their AI career. Below, we’ll delve into tried-and-tested strategies that AI pros employ to drive innovation, foster creativity, and maintain an inspired outlook in an industry that can be both exhilarating and daunting. Whether you’re just starting your AI journey or you’re an experienced professional aiming to sharpen your skills, these insights will help you break out of ruts, discover fresh perspectives, and bring your boldest ideas to life.

Top 10 AI Career Myths Debunked: Key Facts for Aspiring Professionals

Artificial Intelligence (AI) is one of the most dynamic and rapidly growing sectors in technology today. The lure of AI-related roles continues to draw a diverse range of job seekers—from seasoned software engineers to recent graduates in fields such as mathematics, physics, or data science. Yet, despite AI’s growing prominence and accessibility, there remains a dizzying array of myths surrounding careers in this field. From ideas about requiring near-superhuman technical prowess to assumptions that machines themselves will replace these jobs, the stories we hear sometimes do more harm than good. In reality, the AI job market offers far more opportunities than the alarmist headlines and misconceptions might suggest. Here at ArtificialIntelligenceJobs.co.uk, we witness firsthand the myriad roles, backgrounds, and success stories that drive the industry forward. In this blog post, we aim to separate fact from fiction—taking the most pervasive myths about AI careers and debunking them with clear, evidence-based insights. Whether you are an established professional considering a career pivot into data science, or a student uncertain about whether AI is the right path, this article will help you gain a realistic perspective on what AI careers entail. Let’s uncover the truth behind the most common myths and discover the actual opportunities and realities you can expect in this vibrant sector.

Global vs. Local: Comparing the UK AI Job Market to International Landscapes

How to navigate salaries, opportunities, and work culture in AI across the UK, the US, Europe, and Asia Artificial Intelligence (AI) has evolved from a niche field of research to an integral component of modern industries—powering everything from chatbots and driverless cars to sophisticated data analytics in finance and healthcare. The job market for AI professionals is consequently booming, with thousands of new positions posted each month worldwide. In this blog post, we will explore how the UK’s AI job market compares to that of the United States, Europe, and Asia, delving into differences in job demand, salaries, and workplace culture. Additionally, we will provide insights for candidates considering remote or international opportunities. Whether you are a freshly qualified graduate in data science, an experienced machine learning engineer, or a professional from a parallel domain looking to transition into AI, understanding the global vs. local landscape can help you make an informed decision about your career trajectory. As the demand for artificial intelligence skills grows—and borders become more porous with hybrid and remote work—the possibilities for ambitious job-seekers are expanding exponentially. This article will offer a comprehensive look at the various regional markets, exploring how the UK fares in comparison to other major AI hubs. We’ll also suggest factors to consider when choosing where in the world to work, whether physically or remotely. By the end, you’ll have a clearer picture of the AI employment landscape, and you’ll be better prepared to carve out your own path.