[Hiring] Site Reliability Engineer @Assaia

Role Description

We are looking for a Site Reliability Engineer.

• Manage and deploy containerized applications across diverse environments (GKE, EKS, and on-premises Kubernetes).
• Deploy releases to production environments and ensure successful rollouts.
• Maintain and operate complex infrastructure, ensuring high availability and optimal performance through proactive system administration.
• Prepare and synchronize staging environments to mirror production conditions, including configuration adaptation and QC validation support.
• Maintain and enhance monitoring and alerting stacks (Prometheus, Grafana, Alertmanager) to improve system visibility.
• Participate in on-call rotations and perform root-cause analysis (RCA) to resolve production issues and prevent recurrence.
• Design and implement procedures for system troubleshooting, maintenance, and automated recovery.
• Implement and manage InfoSec configurations, including firewall management, backup strategies, and security hardening.
• Provide high-level technical support, resolving complex escalation.
• Collaborate with Project Managers and cross-functional teams to align infrastructure capabilities with project requirements and timelines.
• Research and adopt innovative technologies to continuously improve system reliability, security, and automation.

Qualifications

• 3+ years of proven experience as an SRE, IT Operations Engineer, or Systems Administrator.
• Excellent verbal and written English skills.
• Strong Linux system administration and deep understanding of networking concepts.
• Hands-on experience managing Kubernetes clusters.
• Proficiency with monitoring and alerting stacks (Prometheus, Grafana, Alertmanager).
• Solid understanding of infosec principles and best practices.
• Strong automation mindset with scripting skills in Python, Bash, or similar.
• Ability to manage multiple priorities and work effectively under pressure.
• Pragmatic, responsible, and collaborative approach to problem-solving.

Requirements

• Hands-on experience with on-premises Kubernetes installations.
• Experience with microservice architecture and Helm.
• Experience with Jsonnet for deployment configurations.
• Understanding of Machine Learning, Computer Vision, or AI-based video analytics.
• Familiarity with QA practices and CI/CD workflows.
• Experience using AI tools to enhance automation and productivity.
• Bachelor’s degree in Computer Science, Engineering, or a related field.
• Relevant certifications (CKA/CKAD, AWS, Google Cloud).

Benefits

• Participation in making important decisions, your ideas will be heard and implemented.
• Always remote work and a flexible schedule.
• Paid vacation, paid sick leaves.
• Paid relevant courses/online education.
• Great company culture based on honesty and mutual respect.
• Live team events.