DevOps Engineer

Responsibilities:

- Design and elevate our scalable infrastructure for AI/ML workloads, ensuring top-tier availability for model serving and seamless content processing.

- Develop efficient CI/CD pipelines and implement infrastructure as code using tools like Terraform and CloudFormation to automate provisioning and deployments.

- Be a champion for developer experience by crafting self-service platforms, enhancing internal tooling, and establishing standardized development environments.

- Orchestrate the management of containerized workloads on Kubernetes, expertly handling resource allocation for GPU clusters and video processing tasks.

- Implement robust observability solutions to monitor system health, track LLM costs, and evaluate performance metrics effectively.

- Collaborate closely with engineering teams to promote and optimize DevOps best practices, while also managing cloud costs and maximizing resource utilization.

Requirements:

- A seasoned professional with 4+ years of DevOps/SRE experience and strong expertise in cloud platforms (AWS, GCP, or Azure).

- A proficient user of infrastructure as code tools (Terraform, CloudFormation), containerization technologies (Docker, Kubernetes), and CI/CD methodologies.

- Experience in developer enablement, including building internal tools, fostering self-service platforms, and enhancing developer productivity.

- Strong scripting capabilities in languages such as Python, Bash, or Go, along with hands-on experience in monitoring and observability tools (like Prometheus, Grafana, or DataDog).

- A background in database and messaging systems (PostgreSQL, MongoDB, Redis, Kafka/RabbitMQ) is highly valued.

- Excellent problem-solving abilities and communication skills, with a knack for recognizing and addressing developer pain points.