Ai Infrastructure Architect

Experteer Overview As a hands-on Infrastructure Architect, you design and optimize AI and ML infrastructure powering real-world applications.You will work with senior engineers and lead own workstreams, shaping compute resources, deployment automation, and data pipelines.You’ll balance performance, cost, and scalability while ensuring security and compliance.This role offers ownership over critical AI systems and opportunities to mentor others and drive architectural standards.Compensaciones / Beneficios* Write, review, and debug code, scripts, and infrastructure-as-code for AI infrastructure and tooling* Architect and provision compute resources across cloud and on-premises, including GPU clusters* Design and maintain deployment automation and CI/CD pipelines for AI systems* Deploy AI systems, models, and data pipelines into production and codify best practices* Lead container orchestration and model serving with Docker, Kubernetes, and deployment frameworks* Own AI monitoring and infrastructure health across InfraOps and MLOps* Mentor junior engineers and lead code reviews* Define and document architecture standards and security, cost, and scalability practicesResponsabilidades* Practical experience coding, building, monitoring, and troubleshooting AI/ML applications and deployment infrastructure* Strong understanding of AI/ML concepts and infrastructure for on-premises or public cloud* Proficiency in Python, Java, or C++* Experience with data pipelines/workflow tools (e.g., Apache Airflow, Kubeflow)* Ability to work in a fast-paced environment and collaborate effectively* Proven experience in AI/ML infrastructure engineering or on a hyperscaler platform for large-scale deploymentsRequisitos principales*

• Strong understanding of AI/ML concepts and infrastructure for on-premises or public cloud
• Proficiency in Python, Java, or C++
• Experience with data pipelines/workflow tools (e.g., Apache Airflow, Kubeflow)
• Ability to work in a fast-paced environment and collaborate effectively
• Proven experience in AI/ML infrastructure engineering or on a hyperscaler platform for large-scale deployments