Senior Architect AI

Senior Architect AI Overview

This role sits within Liberty Global’s technology organisation and is focused on shaping the architecture behind AI capabilities used across a large telecommunications environment. The position is responsible for defining and governing the end-to-end AI platform that supports services across a subscriber base of 85 million people. It combines deep technical architecture work with business-facing collaboration, so the successful candidate can ensure AI solutions are not only technically sound but also aligned to operational needs, budget realities, and measurable business outcomes.

What you will do

• Lead the overall design and ownership of the AI platform architecture, including data pipelines, model development, infrastructure, deployment layers, and integration with both on-premises and cloud-based systems and applications.
• Set the long-term technical direction for the platform so it can support current and future requirements across customer experience, AI innovation, and operational efficiency use cases.
• Establish architectural principles, design patterns, and technology selection criteria that enable AI solutions to scale reliably across multiple European markets and ventures.
• Ensure architectural decisions take account of operational constraints, budget limits, and business priorities while still maintaining strong technical standards.
• Own the integration of AI capabilities with Liberty Global’s core telecom infrastructure and associated ventures, making sure data flows smoothly and systems remain dependable.
• Design integration methods and API strategies that connect AI services to existing platforms while preserving security, performance, and data quality.
• Work alongside enterprise architects and engineering teams so AI solutions fit within the wider technology estate and infrastructure capabilities.
• Define monitoring, observability, quality assurance, and operational targets for AI platform components so the environment remains stable and performs as expected.
• Provide architectural guidance to engineers, data scientists, and product managers throughout the lifecycle of AI solution development.
• Collaborate with business stakeholders to gather requirements, turn them into technical designs, and clearly explain trade-offs, delivery timelines, and resource implications.
• Review and approve technical designs, checking that they follow architectural standards and best practices while addressing scalability, security, and maintainability.
• Work with operations teams on deployment planning, capacity forecasting, and cost optimisation for AI infrastructure and cloud resources.
• Support technical due diligence for acquisitions, investments, or partnerships by assessing the AI and technology landscape involved.
• Contribute to budget planning and cost optimisation discussions, including recommendations on infrastructure investment, cloud resource allocation, and technology selection.
• Design solutions that improve operational efficiency through automation, efficient resource use, and smart platform design while still meeting performance requirements.
• Support scaling and capacity decisions using usage patterns, performance metrics, and business growth projections.
• Take part in vendor reviews and technology assessments, offering recommendations that balance capability, cost, and operational impact.
• Improve and refine processes, frameworks, and operating context so the business can achieve the right outcomes.
• Set lifecycle management expectations and oversee end-of-life handling for models and components.
• Help define and validate business cases by establishing clear metrics, measurable outcomes, and return on investment so solutions create customer value and product impact.

What the role requires

• Eight to ten years of experience in software architecture or technical lead roles, with four to five years specifically focused on AI/ML platforms and data-intensive systems.
• Proven experience designing end-to-end architectures or processes for AI/ML systems in production environments that support large user bases.
• Strong knowledge of cloud environments such as AWS, Azure, and GCP, along with containerisation tools like Kubernetes and Docker, and familiarity with MLOps frameworks and practices.
• Understanding of both Waterfall and Agile delivery approaches, including Kanban and SAFe.
• Deep knowledge of telecommunications systems and integration patterns involving OSS/BSS, customer platforms, and network management systems.
• Ability to work effectively with both technical teams and business stakeholders, translating between technical and commercial language.
• Experience with AI/ML technologies such as model training platforms, deployment frameworks, data pipelines, and monitoring tools.
• Background in distributed systems design, API architecture, and microservices patterns for scalable platform development.
• Strong understanding of databases, data warehousing, streaming platforms such as Kafka and Pulsar, and large-scale data processing frameworks.
• Excellent communication and presentation skills, including the ability to explain complex technical ideas to non-technical audiences and business stakeholders using data analysis.
• Understanding of budget planning, cost modelling, and operational considerations for large-scale technology platforms and businesses.
• Ability to source, process, and analyse complex datasets to produce insights that support business and product decisions.
• Hands-on coding and prototyping experience in AI/ML development, particularly with Python, TensorFlow, or PyTorch, would be an advantage.
• Experience building proof-of-concepts and validating new AI technologies would be beneficial.
• Background in data science or machine learning engineering, with an understanding of model development workflows, would be useful.
• Practical experience with infrastructure as code and DevOps practices for AI platforms would be an advantage.
• Knowledge of data management in M&A due diligence would be beneficial.
• Experience in telecommunications, cable, or network infrastructure industries, including subscriber analytics and operational systems, is preferred.
• A bachelor’s or master’s degree in Computer Science, Engineering, Telecommunications, or a related technical field is preferred.
• Hands-on development experience with Python, Java, or similar languages is nice to have, although it is not required for the day-to-day work.
• Knowledge of AI ethics, responsible AI practices, and regulatory requirements relevant to European telecommunications markets, or equivalent knowledge gained through operations experience, is preferred.

Additional context

The role is a full-time position based in London, United Kingdom, and is part of Liberty Global’s technology function. It offers the opportunity to work on AI architecture that supports a major telecom business, with exposure to strategic decisions affecting customer experience, innovation, operations, and corporate development activity such as acquisitions, investments, and partnerships.

Degree Requirement: Bachelor’s

Visa Sponsorship May be