AI Solution Architect - Educational Content Author

About the Role

This opportunity involves blending expertise in AI solution architecture with a passion for technical education and developer advocacy. You will enable developers, researchers, and academic collaborators to effectively utilize advanced cloud infrastructure tailored for AI applications.

Your focus will be on crafting compelling educational materials—ranging from tutorials and reference designs to interactive coding sessions and detailed technical guides. Close cooperation with engineering groups and external partners will be essential to design accessible solutions for intricate AI technologies.

Key Responsibilities

• Develop educational technical content illustrating effective cloud computing use, including virtual machines, GPU clusters, Kubernetes, SLURM, and associated infrastructure.
• Create example code, detailed tutorials, reference architectures, and comprehensive documentation portraying AI and cloud infrastructure best practices.
• Produce video tutorials and live coding demonstrations to enhance developer adoption and comprehension.
• Work alongside academic collaborators and technical stakeholders to gather requirements and design fitting cloud solution architectures.
• Construct and document Infrastructure as Code implementations, technical manuals, and execution resources in partnership with architecture teams.
• Serve as a reliable technical consultant, sharing expertise on GPU cloud technology, AI workloads, and performance optimization.
• Contribute to elevating the developer experience and expanding knowledge about modern AI platforms.

Candidate Requirements

• Minimum 2 years' experience in software development, cloud engineering, DevOps, or related technical fields.
• Proficient understanding of cloud infrastructure, distributed computing, and deployment strategies.
• Practical hands-on experience with virtual machines, containerization, and compute resource management.
• Experience in developing Infrastructure as Code solutions, ideally with Terraform.
• Knowledge of GPU clusters, AI workload management, and methods to optimize machine learning performance.
• Familiarity with Kubernetes, SLURM job schedulers, and container orchestration tools.
• Understanding of key infrastructure components such as networking, storage optimization, and resource allocation.
• Skilled at optimizing diverse workloads within cloud ecosystems.
• Strong programming capabilities in Python, including experience with the PyTorch framework.
• Excellent written communication skills, capable of clarifying complex technical subjects effectively.
• Additional experience with MLflow, Apache Airflow, Kubeflow, cloud machine learning platforms, hybrid cloud setups, or on-prem GPU infrastructure is advantageous.
• Experience collaborating with technology partners, integrating third-party solutions, or publicly presenting technical ideas is a plus.

Benefits

• Attractive and competitive compensation package.
• Opportunities for career advancement and continuous professional development.
• Flexible work environment promoting autonomy and personal responsibility.
• Engagement in significant AI infrastructure and cloud technology projects.
• Collaborative and diverse international team culture.
• Exposure to state-of-the-art AI technologies and complex engineering challenges.
• Unique chance to shape the future landscape of AI development and education.