System Architect

Imagine helping shape the secure cloud, data and AI foundation behind an intelligence engine that supports real-time decision-making and workflow automation in Control Rooms worldwide.

At Barco Control Rooms, you will contribute to software solutions that enable operators across industries such as energy & utilities, transportation, manufacturing, and government to monitor, analyze, and act on complex information streams.

As a System Architect Cloud & Data, you will play a key role in defining and evolving the architecture of a cloud-based data platform within the Barco Control Rooms portfolio, combining strategic architecture leadership with a hands-on approach to technology innovation.

Key Responsibilities

• Define and own the end-to-end software architecture of a cloud data platform within the Barco Control Rooms portfolio.
• Design and evolve secure, scalable, and sovereign cloud architectures.
• Drive the implementation of multi-layered data architectures and data lake solutions.
• Establish, deploy, and maintain architecture design governance practices.
• Stay hands-on with technology through experiments, proofs of concept, technical validations, and code reviews.
• Guide the secure, scalable, and customer-focused integration of AI capabilities into product architectures.
• Assess the opportunities and limitations of AI-assisted and AI-enabled systems and provide architectural guidance.
• Monitor industry and technology developments within cloud, data, AI, and Control Room domains, and advise product management and product owners on technical roadmap decisions.
• Promote a system-wide mindset across software components, teams, and development locations.

Your Profile

• Master’s degree in Computer Science, Software Engineering, or equivalent through experience.
• Proven experience designing and evolving cloud-native software architectures operating at scale.
• Hands-on mindset with experience building proofs of concept, prototypes, experiments, and technical validations.
• Broad software engineering expertise, including serverless architectures, event-driven systems, microservices, APIs, and cloud platforms.
• Strong understanding of cloud architecture principles, including scalability, reliability, observability, security, and cost optimization.
• Knowledge of cloud security fundamentals, identity and access management, data protection, and secure software development practices.
• Understanding of modern AI and machine learning concepts, including large language models, retrieval-augmented generation (RAG), prompt engineering, model evaluation, and AI governance.
• Strong learning mindset with a commitment to staying current on developments in cloud technologies and artificial intelligence.
• Excellent communication, presentation, facilitation, and stakeholder management skills, with the ability to explain vision, trade-offs, risks, and technical concepts to diverse audiences, including executive stakeholders.
• Fluency in spoken and written English.
• Experience with Google Cloud Platform (GCP) and Google AI technologies such as Vertex AI, Gemini, and AI Platform is considered an asset.
• Experience working in international development environments is considered an asset.
• Experience in large-scale agile environments involving multiple teams and product owners is considered an asset.