As Senior Architect AI, you design and oversee Liberty Global’s AI platform to power telecom services for a 85 million subscriber base. You will own the technical vision, ensuring an end-to-end AI architecture that spans data pipelines, model development, and deployment across on-prem and cloud environments. You collaborate with engineering and business stakeholders to translate needs into scalable, secure, and cost-aware solutions. This role focuses on delivering reliable AI capabilities that drive customer value and operational efficiency. You will operate at scale, shaping platform strategy across Europe and guiding cross-functional teams.
Responsibilities
Design and maintain end-to-end AI platform architecture including data pipelines, model development, infrastructure, and deployment across on-prem and cloud
Own the technical vision for AI platform evolution to meet current and future business needs
Define standards, patterns, and tech selection for scalable AI implementations across markets
Ensure architecture aligns with operational, budget, and business priorities while maintaining excellence
Drive AI platform integration with Liberty Global’s telecom infrastructure and ventures, ensuring data flow, security, and reliability
Provide technical guidance to engineering, data science, and product teams throughout the lifecycle
Review and approve designs for scalability, security, and maintainability; align with enterprise architecture
Collaborate on deployment strategies, capacity planning, and cost optimization for AI infra and cloud resources
Support technical due diligence for acquisitions, investments, or partnerships
Define and optimize processes, governance, and lifecycle management for AI components
Establish metrics, ROI, and measurable outcomes to ensure customer value and product impact
Key requirements
8-10 years in software architecture or tech lead roles with 4-5 years in AI/ML platforms and data-intensive systems
Proven track record designing end-to-end AI/ML architectures in production for large user bases
Experience with cloud platforms (AWS, Azure, GCP), containerization (Kubernetes, Docker), and MLOps practices
Knowledge of Agile/Waterfall methodologies and scaling with Kanban or SAFE
Deep understanding of telecom systems and OSS/BSS integration patterns
Strong ability to translate technical concepts for business stakeholders
Proficiency in AI/ML tech including model training, deployment, data pipelines, and monitoring
Experience with distributed systems, API/microservices, and data warehousing
Knowledge of streaming platforms (Kafka, Pulsar) and big data processing
Budget planning, cost modeling, and operational considerations for large-scale platforms
Ability to source, process, and analyze complex datasets for business decisions
Desirable: hands-on coding in Python, TensorFlow, PyTorch; PoC development; IaC and DevOps for AI platforms
Education in telecom, CS/Engineering preferred
Nice to have: knowledge of AI ethics and regulatory considerations for Europe
strong communication and presentation skills
cross-functional collaboration
ability to translate between technical and business language
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