Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

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

London
9 months ago
Applications closed

Related Jobs

View all jobs

Machine Learning Infrastructure Engineer

Cloud Engineer

Machine Learning Engineer

Machine Learning Engineer

Lead Software Engineer - Python / AWS / MLOps

Lead Software Engineer - Python / AWS / MLOps

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)

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.

How to Write an AI CV that Beats ATS (UK examples)

Writing an AI CV for the UK market is about clarity, credibility, and alignment. Recruiters spend seconds scanning the top third of your CV, while Applicant Tracking Systems (ATS) check for relevant skills & recent impact. Your goal is to make both happy without gimmicks: plain structure, sharp evidence, and links that prove you can ship to production. This guide shows you exactly how to do that. You’ll get a clean CV anatomy, a phrase bank for measurable bullets, GitHub & portfolio tips, and three copy-ready UK examples (junior, mid, research). Paste the structure, replace the details, and tailor to each job ad.

AI Recruitment Trends 2025 (UK): What Job Seekers Must Know About Today’s Hiring Process

Summary: UK AI hiring has shifted from titles & puzzle rounds to skills, portfolios, evals, safety, governance & measurable business impact. This guide explains what’s changed, what to expect in interviews, and how to prepare—especially for LLM application, MLOps/platform, data science, AI product & safety roles. Who this is for: AI/ML engineers, LLM engineers, data scientists, MLOps/platform engineers, AI product managers, applied researchers & safety/governance specialists targeting roles in the UK.

Why AI Careers in the UK Are Becoming More Multidisciplinary

Artificial intelligence is no longer a single-discipline pursuit. In the UK, employers increasingly want talent that can code and communicate, model and manage risk, experiment and empathise. That shift is reshaping job descriptions, training pathways & career progression. AI is touching regulated sectors, sensitive user journeys & public services — so the work now sits at the crossroads of computer science, law, ethics, psychology, linguistics & design. This isn’t a buzzword-driven change. It’s happening because real systems are deployed in the wild where people have rights, needs, habits & constraints. As models move from lab demos to products that diagnose, advise, detect fraud, personalise education or generate media, teams must align performance with accountability, safety & usability. The UK’s maturing AI ecosystem — from startups to FTSE 100s, consultancies, the public sector & universities — is responding by hiring multidisciplinary teams who can anticipate social impact as confidently as they ship features. Below, we unpack the forces behind this change, spotlight five disciplines now fused with AI roles, show what it means for UK job-seekers & employers, and map practical steps to future-proof your CV.