Senior System Architect ML & AI 100% (f/m/d)
On-siteZürich, Zurich, Switzerland
Job Summary
Design and own end-to-end solution architectures for enterprise AI and ML applications, ensuring alignment with target architectures and business priorities. Initiate and document architecture decisions as approved records, while advising engineers on technical feasibility and implementation. Drive hands-on architectural design for AI platforms, balancing consistency with delivery needs for initiatives like the AI automation orchestration layer. Proactively identify risks, dependencies, and technical debt, then escalate them to leadership. Contribute to PI Planning, backlog refinement, and roadmap discussions, acting as the primary architectural contact for assigned teams.
Required Qualifications
- At least 3 years of experience as a Senior Architect in complex IT environments
- At least 5 years of experience as a Lead or Senior Software Engineer
- hands-on responsibility including practical experience with AI/ML solutions and platforms
- Responsible for solution architectures: from design and implementation to operation
- Ability to identify options for solution architectures and make trade-off architecture decisions
- Collaboratively develop and coordinate solutions with business and technology stakeholders and architecture colleagues
- Proactive mindset, able to work under pressure and meet deadlines
- Practical experience designing and delivering AI and ML solutions in scalable enterprise platforms
- Strong understanding of AI/ML solution patterns, data pipelines, orchestration, and platform integration
- Ability to translate ART- and domain-level target architectures into practical, team-level solution designs
- Experience working across multiple teams while maintaining architectural alignment and consistency
- Ability to identify architectural risks and technical debt early and address them constructively
- Strong communication skills, with the ability to clearly explain architectural topics to both technical and non-technical stakeholders
- Bachelor's or Master's degree in Computer Science, Engineering, or a comparable field
- Solid foundation in software and system architecture, including modern architectural styles such as event-driven architectures, microservices, and modular monoliths
- Strong understanding of distributed systems, APIs, and platform integration patterns
- Practical familiarity with AI/ML platforms and ecosystems, including data pipelines, orchestration, and model lifecycle concepts
- Experience working with CI/CD pipelines, DevOps practices, and operational considerations in production environments
- Ability to work effectively in agile and SAFe environments using common collaboration and delivery tooling
- English: business fluent
Desired Qualifications
- Additional certifications are an advantage (e.g. SAFe, cloud, architecture, or AI/ML-related certifications)
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