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

Apply Now

Tangent International | Director of Architecture

Tangent International
Edinburgh
10 months ago
Applications closed

Director of Architecture


Director of Architecture, Join a pioneering leader in the financial crime and fraud prevention sector as a Director of Architecture. In this role, you’ll define and implement advanced, machine learning-driven solutions, guiding an agile team to ensure performance, scalability, and architectural integrity. This is a unique opportunity to build a next-generation machine learning platform from the ground up, ensuring robust fraud detection and prevention for financial institutions worldwide.


Role Overview


As the Director of Architecture, you’ll lead transformative machine learning initiatives, leveraging your expertise to design and oversee a high-performance, cloud-native fraud detection platform. This role is ideal for a strategic leader with a hands-on approach, combining deep knowledge of enterprise and solution architecture with a track record in machine learning platform development. You’ll also champion a culture of continuous innovation and growth within a close-knit team that embraces wearing multiple hats.


Key Responsibilities


  • Build and Lead: Architect and implement a machine learning platform that integrates seamlessly with existing solutions, enhancing real-time fraud detection capabilities.
  • Define and Drive Transformation: Establish a clear machine learning architecture roadmap, working closely with engineering teams to bring strategic solutions from concept through full implementation.
  • Hands-On Leadership: Lead a small team, staying hands-on while overseeing all phases of architecture from enterprise to solution level, ensuring agility and innovation remain at the forefront.
  • End-to-End Product Lifecycle: Drive product development through the entire lifecycle, implementing machine learning solutions that improve fraud detection accuracy and system scalability.
  • Collaborate for Strategic Alignment: Partner with Product, Engineering, and Operations to ensure machine learning projects are aligned with business objectives and optimized for high-volume, low-latency environments.
  • Enterprise and Real-Time Architecture Expertise: Create high-availability systems for fraud prevention, leveraging your knowledge of real-time machine learning architecture for critical, low-latency solutions.


Must-Have Technical Experience


  • Machine Learning Platform Development: Proven success in building machine learning architectures from the ground up within enterprise environments.
  • Enterprise to Solution Architecture Expertise: Ability to conceptualize and guide the transition from high-level enterprise architecture to actionable solution architecture.
  • Fraud Prevention Background: At least 5 years of experience within the fraud prevention domain, implementing or overseeing machine learning initiatives.
  • Cloud Architectures and Data Science Knowledge: Proficiency in cloud-based infrastructures, SaaS architectures, and familiarity with machine learning concepts.
  • SAFe Experience:Proven experience working within a SAFe (Scaled Agile Framework) environment, with a strong understanding of agile methodologies at scale.



Ideal Profile


  • 10+ years of architecture experience, ideally combining bothenterpriseandsolution architecturebackgrounds.
  • 5+ years leading small, agile teams (5 people or fewer), with hands-on involvement in development and project oversight.
  • Strong Communication and Collaboration: Skilled at aligning technical strategies with business objectives and comfortable presenting to senior leadership and external stakeholders.
  • SAFe Experience:Proven experience working within a SAFe (Scaled Agile Framework) environment, with a strong understanding of agile methodologies at scale.

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

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Jobs

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Jobs

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.

🍪 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.