Senior Systems Engineer

Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI’s potential impact on the function or industry.
Typically requires a minimum of 5 years of related experience with a Bachelor’s degree; or 3 years and a Master’s degree; or a PhD without experience; or equivalent work experience.
Strong hands-on experience with at least one major hyperscaler (GCP preferred; AWS and Azure also valuable).
Proficient in Linux system administration and debugging.
Experience with infrastructure automation tools (Puppet, Ansible).
Solid scripting and automation skills with a developer mindset.
Familiarity with Git and code-based deployment workflows.
Ability to work in a fast-paced environment where priorities shift frequently.
Excellent problem-solving skills, curiosity, and ability to work without a predefined solution path.

Collaborate with cloud providers (Azure, AWS, GCP) to support migrations and new deployments.
Design, test, and validate new server SKUs in partnership with Technical Account Managers and engineering teams.
Work closely with QE and System Engineering to debug cloud service issues, identifying root causes and working with providers like Azure for resolution.
Automate server deployment and scaling processes using tools such as Puppet, Ansible, and Git.
Troubleshoot and resolve tier-3 customer performance issues with a strong emphasis on debugging and root cause analysis.
Act as a technical point of contact for hyperscaler integration issues, particularly for database nodes and performance validation.
Balance short-term customer-driven priorities with long-term capacity planning and automation improvements.