Staff Site Reliability Engineer

Soft skills

• Communication: Clear, concise communication skills and a bias for collaborative problem-solving.
• Leadership Alignment: Proven track record of guiding multi-stakeholder initiatives and influencing engineering practices across teams.
• Analytical Rigor: Strong problem-solving, debugging, and analytical skills, especially in high-pressure environments.

Education & certifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• Relevant certifications (CKA/CKAD, AWS/GCP Professional Cloud Architect, etc.) are a plus.

WHY JOIN US?

• Opportunity to work with cutting-edge AI-driven cybersecurity technologies and Google SecOps solutions.
• Collaborate with a talented and innovative team focused on continuously improving security operations and system reliability.
• Competitive salary and benefits package.
• A culture of growth and development, with opportunities to expand your knowledge in AI, cybersecurity, and emerging technologies.

If you're passionate about building resilient infrastructure, scaling AI systems, and working at the intersection of reliability and security, we encourage you to apply!

• Domain Background: Prior work in cybersecurity, specifically regarding SIEM, EDR, or SOAR infrastructure.
• AI/ML Infrastructure: Experience supporting infrastructure for large-scale AI/ML workloads (e.g., GPU scheduling, LLM serving optimization).
• Startup Mentality: Background driving high-impact engineering initiatives in high-growth startups or enterprise SaaS.
• Strong familiarity with Agentic Workflows such as Agno, Temporal, etc..

• System Resilience: Design, build, and maintain highly available, scalable, and secure infrastructure to support our AI-native cybersecurity platform.
• Automation & Tooling: Develop internal tooling and automation to streamline deployment processes, incident response, and capacity planning.
• Performance Engineering: Monitor system performance and proactively identify bottlenecks, optimizing infrastructure for low-latency, high-throughput AI workloads.
• Incident Management: Lead incident response efforts, conduct post-mortems, and implement long-term solutions to prevent recurring reliability issues.
• Infrastructure as Code (IaC): Manage infrastructure via code, driving consistency, auditability, and scalability across our cloud environments (e.g., AWS, GCP).
• Cross-Functional Collaboration: Partner with sibling Engineering teams, Product, and Security teams to ensure reliability is baked into our development lifecycle from concept to production.

• Core Engineering: 10+ years of experience in SRE, DevOps, or Software/Systems Engineering, particularly in managing production systems at scale.
• Cloud Infrastructure: Deep expertise in public cloud environments (AWS, GCP, or Azure) and managing services such as Kubernetes (EKS/GKE), networking, and storage.
• Infrastructure as Code: Extensive experience with tools like Terraform, Pulumi, or similar technologies to manage complex infrastructure deployments.
• Observability: Hands-on experience with monitoring, logging, and tracing stacks (e.g., Prometheus, Grafana, ELK, Datadog) to drive data-informed reliability decisions.
• Distributed Systems: Solid understanding of microservices architecture, distributed databases, and event-driven systems.