Senior Architect AI

Senior Architect AI Overview

As a Senior Architect AI, you will be responsible for designing and overseeing the architecture of the AI platform that supports Liberty Global’s telecommunications services for a subscriber base of 85 million. Your role will involve ensuring that AI solutions integrate effectively with the telecommunications infrastructure while adhering to operational, budgetary, and performance standards. This position requires a blend of technical expertise and strong communication skills to engage with both engineering teams and business stakeholders, translating complex technical concepts into actionable insights that drive business results.

Key Responsibilities

• Design and maintain a comprehensive AI platform architecture that includes 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 meets current and future business needs across customer experience, innovation, and operational efficiency.
• Define architectural standards, design patterns, and technology selection criteria 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 that connect AI services with existing platforms while ensuring security, performance, and data quality.
• Collaborate with enterprise architects and engineering teams to align AI solutions with the overall technology architecture and infrastructure capabilities.
• Establish output goals, 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 and translate them into technical architectures, clearly communicating trade-offs, timelines, and resource needs.
• Review and approve technical designs to ensure they align with architectural standards and best practices, 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 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 resource utilization while meeting performance requirements.
• Support capacity planning and infrastructure scaling decisions based on usage patterns and performance metrics.
• Participate in vendor evaluations and technology assessments, offering technical recommendations that balance capability, cost, and operational impact.
• Define and refine processes and frameworks to ensure the right business outcomes.
• 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 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 for AI/ML systems in production environments supporting large user bases.
• Understanding of IT platforms, including cloud services (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 and network management systems.
• Ability to effectively communicate and collaborate with both technical teams and business stakeholders.
• 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 for scalable platforms.
• Strong knowledge of database technologies, data warehousing, streaming platforms, 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 analyze complex datasets to generate actionable insights for business and product decisions.

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 and M&A due diligence.

Preferred Education/Qualifications:

• Experience in telecommunications, cable, or network infrastructure industries with an 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.
• Experience with architectural frameworks and documentation practices for enterprise-scale systems.

Degree Requirement: Bachelor’s

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