Senior Architect AI

Senior Architect AI Overview

As a Senior Architect AI, you will be responsible for the design and oversight of the AI platform architecture that supports Liberty Global’s telecommunications services for a subscriber base of 85 million. This role requires a blend of technical expertise and strong communication skills to effectively collaborate with engineering teams and business stakeholders, ensuring that AI solutions integrate seamlessly with existing telecommunications infrastructure while meeting operational, budgetary, and performance requirements.

Key Responsibilities

• Design and maintain a comprehensive architecture for the AI platform, covering data pipelines, model development, infrastructure, deployment frameworks, and integration with both on-premises and cloud applications.
• Own the technical vision for the evolution of the AI platform, ensuring it aligns with current and future business needs across customer experience, innovation, and operational efficiency.
• Define architectural standards, design patterns, and criteria for technology selection to enable scalable and reliable AI implementations across various European markets.
• Ensure that architectural decisions take into account operational requirements, budget constraints, and business priorities while maintaining high technical standards.
• Oversee the integration of the AI platform with Liberty Global’s core telecommunications infrastructure, ensuring seamless data flow and system reliability.
• Design integration patterns and API strategies to connect AI services with existing platforms while upholding security, performance, and data quality standards.
• Collaborate with enterprise architects and engineering teams to ensure AI solutions are in line with the overall technology architecture and infrastructure capabilities.
• Establish goals for output, monitoring, observability, and quality assurance practices for AI platform components to ensure operational stability and performance targets are met.
• Provide technical expertise and architectural guidance to engineering teams, data scientists, and product managers throughout the AI solution development lifecycle.
• Work closely with business stakeholders to understand their requirements, translate them into technical architectures, and communicate trade-offs, timelines, and resource needs effectively.
• Review and approve technical designs to ensure they align with architectural standards and best practices while addressing scalability, security, and maintainability concerns.
• Collaborate with operations teams on deployment strategies, capacity planning, and cost optimization for AI infrastructure and cloud resources.
• Support comprehensive technical due diligence for potential acquisitions, investments, or partnerships.
• Contribute to budget planning and cost optimization discussions, providing recommendations on infrastructure investments and cloud resource allocation.
• Design architectures that enhance operational efficiency through automation and smart platform design while meeting performance requirements.
• Support capacity planning and infrastructure scaling decisions based on usage patterns, performance metrics, and business growth projections.
• Participate in vendor evaluations and technology assessments, providing technical recommendations that balance capability, cost, and operational impact.
• Define and refine processes and frameworks to ensure the right business outcomes are achieved.
• Set lifecycle management expectations and govern end-of-existence models and components.
• Define and validate business cases by establishing clear metrics and measurable outcomes to ensure solutions deliver tangible customer value.

Knowledge and Experience

Essential:

• 8-10 years of experience in software architecture or technical lead roles, with 4-5 years focused on AI/ML platforms and data-intensive systems.
• Proven experience in designing end-to-end architectures or processes for AI/ML systems in production environments supporting large user bases.
• Understanding of IT platforms, including cloud platforms (AWS, Azure, GCP), containerization (Kubernetes, Docker), and MLOps frameworks.
• Familiarity with both Waterfall and Agile methodologies, including Kanban and SAFE.
• Deep understanding of telecommunications systems and integration patterns with OSS/BSS, customer platforms, and network management systems.
• Ability to effectively communicate with both technical teams and business stakeholders, translating between technical and business language.
• Proficiency in AI/ML technologies, including model training platforms, deployment frameworks, data pipelines, and monitoring tools.
• Experience with distributed systems design, API architecture, and microservices patterns for scalable platforms.
• Strong knowledge of database technologies, data warehousing, streaming platforms (Kafka, Pulsar), and big data processing frameworks.
• Excellent communication and presentation skills for conveying complex technical concepts to non-technical audiences.
• Understanding of budget planning, cost modeling, and operational considerations for large-scale technology platforms.
• Ability to source, process, and analyze complex datasets to generate actionable insights.

Desirable:

• Hands-on coding and prototyping experience in AI/ML development (Python, TensorFlow, PyTorch).
• Experience with proof-of-concept development and technical validation of new AI technologies.
• Background in data science or machine learning engineering with an understanding of model development workflows.
• Practical experience with infrastructure-as-code and DevOps practices for AI platforms.
• Knowledge of data management M&A due diligence.

Preferred education/qualifications:

• Experience in telecommunications, cable, or network infrastructure industries with understanding of subscriber analytics and operational systems.
• Bachelor’s or Master’s degree in Computer Science, Engineering, Telecommunications, or a related technical field.
• Background in hands-on development with Python, Java, or similar languages (nice to have but not required for day-to-day work).
• Knowledge of AI ethics, responsible AI practices, and regulatory requirements relevant to European telecommunications markets or relevant knowledge gained from operations.
• Experience with architectural frameworks and documentation practices for enterprise-scale systems.

Degree Requirement: Bachelor’s

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