This Principal Site Reliability Engineer role focuses on designing and architecting robust infrastructure and services to guarantee optimal reliability and functionality. The position involves forecasting demand, managing capacity needs, and collaborating closely with software development teams to build scalable and resilient infrastructures. You will utilize advanced knowledge for incident response, maintenance, and comprehensive health and performance reporting. Identifying and implementing automation opportunities is key, along with effectively communicating service details and anticipating the impact of changes. The role also includes providing support for technology and documenting incidents, while staying at the forefront of site reliability trends through experimentation and continuous learning.

Key responsibilities include designing and architecting infrastructure for reliability and functionality, forecasting demand, and managing capacity. You will collaborate with development teams to ensure scalable infrastructures, prototype new solutions, and exercise judgment in data collection for operations optimization. Responsibilities also encompass incident response, root cause analysis, and maintenance tasks, along with providing health and performance reporting. Identifying and implementing automation opportunities is crucial, as is developing and implementing automation tools and scripts. You will write release notes, communicate service information, and articulate the impact of changes. Providing operational support, participating in on-call duties, executing technical issue resolution, and conducting root cause analyses are also core duties. Experimentation with new tools and continuous improvement of performance and reliability are expected.

This role requires a minimum of 5 years of hands-on experience in software development, site reliability engineering, monitoring, and automation, with a proven track record of owning production platforms. Strong proficiency in Python is essential, coupled with experience in backend services, REST APIs, integrations, and event-driven workflows. You must have proven experience in building monitoring and observability solutions, integrating AI/LLM capabilities for incident analysis, and developing reusable agents. Experience with alert correlation, automated remediation workflows, and integrating monitoring platforms is mandatory. A strong understanding of distributed systems, Linux, networking, databases, and application performance is required, alongside expertise in software engineering practices like automated testing and CI/CD. Excellent communication and collaboration skills are vital. Experience with agentic AI frameworks, anomaly detection, and observability platforms are beneficial.