AI Systems Engineer - DevOps& Observability Manager

About this kind of role

What a AI Systems Engineer - DevOps& Observability Manager usually does. The employer's own details are in the listing.

Typically does: This role focuses on the design, implementation, and maintenance of infrastructure supporting artificial intelligence systems, with a strong emphasis on DevOps practices and observability. Responsibilities include automating deployment pipelines, monitoring system performance, and ensuring the reliability and scalability of AI infrastructure. The engineer will collaborate with data scientists and machine learning engineers to optimize the AI development lifecycle. Troubleshooting and resolving production issues related to AI systems and their underlying infrastructure are also key aspects.

Tools and skills: Proficiency in cloud platforms (e.g., AWS, Azure, GCP), containerization technologies (Docker, Kubernetes), scripting languages (Python, Bash), configuration management tools (Ansible, Terraform), and observability platforms (Prometheus, Grafana) is generally expected.

Good fit for: Individuals with a strong background in DevOps, systems engineering, and a passion for enabling AI innovation thrive in this role.