Staff Site Reliability Engineer

You will Bring

• 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.

Required Skills & Qualifications

Sre & Infrastructure Expertise

• 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.

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.

Nice-to-have

• 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..

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.