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

Apply Now

Principal Cloud Architect

ZipRecruiter
London
10 months ago
Applications closed

Related Jobs

View all jobs

Principal Data Scientist

Principal Data Scientist

Machine Learning Engineer

Principal Machine Learning (ML) Developer

Principal Machine Learning Engineer

Principal Data Scientist

Job Description

I’m supporting a Google Cloud premier partner consultancy in AI, that empowers world-class businesses with cutting-edge data solutions in the cloud. They have won GCP cloud partner of the year on several occasions. By blending their expertise in machine learning, data engineering, and analytics, they help clients push the boundaries of technology. Using GCP as the foundation, they deliver future-proofed solutions that enhance consumer insights, improve competitive advantage, and optimise operational efficiency.

The Role

As a Principal Cloud Architec, you be pivotal in shaping the architectural direction of key projects. You’ll collaborate with clients to provide pre- and post-sales architectural guidance and thought leadership for machine learning, analytics, and data migration projects. Additionally, you will help define the architectural framework for next- machine learning products.

This is a unique opportunity for an experienced cloud professional to work as part of a team of AI and data experts. You will act as an SME in cloud and solution architecture, working closely with both business and technical stakeholders. The role requires a strong background in Computer Science and experience designing and implementing complex cloud platforms, particularly on Google Cloud or AWS.

To excel in this role, you will need

  • A BSc or MSc in Computer Science or a related field.
  • Proven experience designing and implementing large-scale cloud architectures.
  • Strong analytical and technical capabilities, with an innovative mindset.
  • Excellent communication skills, with the ability to present concepts clearly to a variety of audiences.
  • Experience in end-to-end production-grade cloud technologies, including areas such as data, security, and networking.
  • Proficiency in programming such as Python, Java, and SQL, with the ability to build scalable and high-performing code.
  • Experience in technical pre-sales, including crafting and presenting innovative proposals to clients.

Desirable Skills

  • Google Cloud or AWS Solutions Architect certification.
  • Familiarity with ETL tools, Hadoop-based technologies (e.g., Spark), and data pipelines (e.g., Beam, Flink).
  • Experience designing data lake and data warehouse solutions (e.g., BigQuery, Azure Synapse, Redshift).
  • Hands-on experience with visualisation tools (e.g., Looker, Tableau, PowerBI).
  • Understanding of Agile methodologies such as Scrum.
  • Knowledge of data science concepts like machine learning, data mining, and visualisation.
  • Contributions to open-source projects.

#J-18808-Ljbffr

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

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.

Jobs

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.

Jobs

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.

🍪 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.