Principal Architect

Fractal
London
1 year ago
Applications closed

Related Jobs

View all jobs

Principal Machine Learning Engineer – Production Systems

Principal Machine Learning Engineer - Production Systems

Principal Data Scientist, ML Strategy & Personalization

Prinicipal Data Scientist

Principal Data Scientist

Principal Machine Learning Engineer

. Principal Architect page is loadedPrincipal Architect****Principal ArchitectlocationsLondon time typeFull time posted onPosted Today time left to applyEnd Date: March 31, 2025 (30+ days left to apply) job requisition idSR-29266 It's fun to work in a company where people truly BELIEVE in what they are doing!We're committed to bringing passion and customer focus to the business.Principal ArchitectFractal is a strategic AI partner to Fortune 500 companies with a vision to power every human decision in the enterprise. Fractal is building a world where individual choices, freedom, and diversity are the greatest assets. An ecosystem where human imagination is at the heart of every decision. Where no possibility is written off, only challenged to get better. We believe that a true Fractalite is the one who empowers imagination with intelligence. Fractal has been featured as a Great Place to Work by The Economic Times in partnership with the Great Place to Work Institute and recognized as a ‘Cool Vendor’ and a ‘Vendor to Watch’ by Gartner.Please visit for more information about FractalLocation:London, UKResponsibilities:* Evaluate the current technology landscape and recommend a forward-looking, short, and long-term technology strategic vision.* Engage with senior technical leaders at the client site, becoming a trusted thought partner by understanding their challenges and providing strategic guidance.* Build and maintain strong relationships with senior client leaders and cross-functional stakeholders.* Proactively understand client needs and align them with Fractal’s value propositions, proposing innovative and comprehensive solutions.* Collaborate with offshore delivery teams and other multidisciplinary teams within Fractal to ensure seamless integration and delivery of solutions.* Be willing to take a hands-on approach to understand complex contexts and underlying client requirements.* Participate in the creation and sharing of best practices, technical content, and new reference architectures.* Provide technical architecture leadership and direction on projects, ensuring secure, scalable, reliable, and maintainable platforms.* Work with data engineers and data scientists to develop architectures and solutions.* Assist in ensuring the smooth delivery of services, products, and solutions, while balancing immediate client needs with long-term technical strategy.Success Profile:* In-depth experience as an Architect with expertise in Google Cloud Platform and a passion for applying the latest technologies to solve complex business problems. An ideal candidate would have:* 12+ years of experience in Data Engineering and Cloud Native technologies (including Google Cloud Platforms), covering big data, analytics, and AI/ML domains.* Extensive experience with GCP tools and technologies, including BigQuery, Cloud Composer, Data Flow, Cloud Storage, Vertex AI, and Dataproc.* Expertise in creating, deploying, configuring, and scaling applications on GCP serverless infrastructure.* Strong knowledge and working experience in Data Engineering, Data Management, and Data Governance.* Proven track record of delivering multiple end-to-end Data Engineering, Data Warehousing, or Analytics projects.* Knowledge of general programming languages and frameworks, particularly Python and/or Java.* Familiarity with general technology best practices and development lifecycles such as Agile and CI/CD, as well as DevOps and MLOps for more efficient data and machine learning pipelines.* Ability to design and implement future-proof, complex global solutions using GCP services.* Hands-on experience with foundational architectures, including microservices, event-driven systems, and event streaming, and online machine learning systems.* Excellent communication and influencing skills, with the ability to adapt messages to various audiences and build consensus.Preferred Qualifications* Experience in container technologies, specifically Docker and Kubernetes.* Experience or knowledge of DevOps on GCP.* Google Cloud Professional Cloud Architect Certification.* Demonstrated ability to navigate complex stakeholder environments and build strong, lasting relationships.* Hands-on approach and willingness to delve into technical details to understand the full context of a problem and ensure the best solutions are provided.* Experience with AWS, especially in the context of hybrid cloud setups.Fractal provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!Introduce Yourselfin the top-right corner of the page or create an account to set up email alerts as new job postings become available that meet your interest!#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.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.

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

Changing career into artificial intelligence in your 30s, 40s or 50s is no longer unusual in the UK. It is happening quietly every day across fintech, healthcare, retail, manufacturing, government & professional services. But it is also surrounded by hype, fear & misinformation. This article is a realistic, UK-specific guide for career switchers who want the truth about AI jobs: what roles genuinely exist, what skills employers actually hire for, how long retraining really takes & whether age is a barrier (spoiler: not in the way people think). If you are considering a move into AI but want facts rather than Silicon Valley fantasy, this is for you.