AI Principal
HybridPorto, Porto, Portugal
Job Summary
Ensure technical consistency of AI solutions and their portability across target environments by acting as the custodian of architectural standards. In collaboration with data, IT, and business stakeholders, establish robust foundations guaranteeing scalability, reliability, security, and trust. Advise on solution design and target architecture for AI applications, guiding teams towards sound, future-proof technical choices. Contribute to drafting technical specifications, follow up on development progress, and oversee acceptance testing to ensure solutions meet quality and performance standards. Oversee the seamless integration, management, and scaling of AI systems, coordinating between data teams, IT, and business functions. Monitor AI infrastructure performance, manage costs, and ensure operational reliability, including scheduling model updates and managing dependencies. Participate in project governance and technical forums, ensuring architectural decisions are well-documented. Proactively identify technical risks and propose mitigation strategies to protect delivery timelines and solution integrity.
Required Qualifications
- 8 years of professional experience
- at least 5 years of experience in DevOps
- at least 5 years of experience in cloud infrastructure
- at least 5 years of experience in IT architecture
- meaningful hands-on exposure to AI tooling and platforms
- Solid understanding of AI and ML components
- Solid understanding of model serving
- Solid understanding of data pipelines
- Solid understanding of vector databases
- Solid understanding of orchestration frameworks
- Proven experience setting architectural standards or reference architectures across multiple teams or projects
- Experience reviewing, challenging, and approving technical decisions made by other engineers or vendors
- Experience with major cloud providers (Azure, AWS, or GCP)
- strong preference for candidates familiar with Azure and Databricks
- Proficiency in infrastructure-as-code
- Proficiency in CI/CD pipelines
- Proficiency in containerisation (Docker, Kubernetes)
- Proficiency in monitoring tooling
- Good understanding of data architecture principles
- Good understanding of data warehousing
- Good understanding of data lakes
- Good understanding of governance frameworks
- Ability to translate technical constraints and risks into clear language for business and project stakeholders
- Strong attention to detail
- systematic approach to quality assurance and testing
- Fluency in English
Desired Qualifications
- Experience in international, consulting, or scale-up environments
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