We're hiring a Senior/Principal Site Reliability Engineer to own production reliability for Cortex Agentix Endpoint Security (following an acquisition of KOI Start Up) as it scales. You'll define and operate our SLOs and error budgets, lead high-severity incident response, and ensure our Kubernetes and AWS infrastructure stays stable under growth. You'll also build and supervise the AI agents that handle routine alert triage and monitor tuning, focusing your own time on the reliability engineering that requires human judgment. This role is a strong fit for someone who treats reliability as an engineering discipline and enjoys ownership, incident command, and applying AI to operational work.
Your Impact:
Own reliability as an engineering discipline – define SLIs, set SLOs, and run error-budget-based decision-making so "how reliable are we" becomes a number that governs how fast we ship.
Own production incidents end-to-end – lead response, mitigation, and resolution for high-severity incidents, and drive blameless postmortems that feed real fixes back into the system.
Own the reliability and capacity of production infrastructure as we scale – forecasting headroom, validating scaling behavior under load, and keeping latency and error rates within SLO.
Run and evolve Kubernetes environments so releases and infra changes are safe by default across hundreds of tenant apps.
Own, build, and supervise our SRE AI agents that triage alerts, review monitors, resolves and summarize incidents. Set and expand the trust ladder that governs what the agents do autonomously, what needs approval, and what stays human. This is a core part of the role.
Improve observability and incident response – raise signal quality, cut alert noise, and own the monitoring the triage agents depend on.
Eliminate toil – relentlessly identify manual, repetitive operational work and remove it through automation and agents, protecting engineering time for reliability work that only humans can do.
Analyze operational data across incidents, alerts, deployments, infra health, and cost to find reliability gaps, capacity risks, and automation opportunities.
Evaluate and introduce new tools and AI-assisted approaches, balancing innovation with reliability, cost, and operational simplicity.
Your Impact:
Own reliability as an engineering discipline – define SLIs, set SLOs, and run error-budget-based decision-making so "how reliable are we" becomes a number that governs how fast we ship.
Own production incidents end-to-end – lead response, mitigation, and resolution for high-severity incidents, and drive blameless postmortems that feed real fixes back into the system.
Own the reliability and capacity of production infrastructure as we scale – forecasting headroom, validating scaling behavior under load, and keeping latency and error rates within SLO.
Run and evolve Kubernetes environments so releases and infra changes are safe by default across hundreds of tenant apps.
Own, build, and supervise our SRE AI agents that triage alerts, review monitors, resolves and summarize incidents. Set and expand the trust ladder that governs what the agents do autonomously, what needs approval, and what stays human. This is a core part of the role.
Improve observability and incident response – raise signal quality, cut alert noise, and own the monitoring the triage agents depend on.
Eliminate toil – relentlessly identify manual, repetitive operational work and remove it through automation and agents, protecting engineering time for reliability work that only humans can do.
Analyze operational data across incidents, alerts, deployments, infra health, and cost to find reliability gaps, capacity risks, and automation opportunities.
Evaluate and introduce new tools and AI-assisted approaches, balancing innovation with reliability, cost, and operational simplicity.
Requirements:
Your Experience:
5+ years operating production cloud infrastructure, with a strong reliability focus (SRE, or DevOps/platform engineering with reliability ownership).
Deep hands-on experience with Kubernetes, Helm, ArgoCD, Terraform, and CI/CD.
Experience defining and operating SLIs, SLOs, and error budgets – or a clear grasp of the discipline and the drive to establish it from scratch.
Strong observability and alerting experience in Datadog or comparable platforms, including raising signal-to-noise in production.
Proven incident-response instincts – comfortable owning high-severity incidents and a genuine believer in blameless postmortems.
Proven ability to own platform and reliability projects end-to-end, from design through production operation and ongoing improvement.
Strong troubleshooting across distributed systems, Kubernetes, CI/CD, and live incidents.
Collaborative mindset – comfortable working across engineering, security, product, and leadership.
Comfort in a fast-paced, high-ownership environment where priorities shift but production quality doesn't.
Genuine interest in applying AI, automation, and intelligent workflows to operational work – and in building and supervising agents, not just using them.
Ownership-driven – You take responsibility for the reliability of the systems you build and operate, from SLO definition through incident command and continuous improvement.
Reliability as engineering – You treat reliability as a software problem to be solved with code, measurement, and automation – not an ops queue to be worked by hand.
Your Experience:
5+ years operating production cloud infrastructure, with a strong reliability focus (SRE, or DevOps/platform engineering with reliability ownership).
Deep hands-on experience with Kubernetes, Helm, ArgoCD, Terraform, and CI/CD.
Experience defining and operating SLIs, SLOs, and error budgets – or a clear grasp of the discipline and the drive to establish it from scratch.
Strong observability and alerting experience in Datadog or comparable platforms, including raising signal-to-noise in production.
Proven incident-response instincts – comfortable owning high-severity incidents and a genuine believer in blameless postmortems.
Proven ability to own platform and reliability projects end-to-end, from design through production operation and ongoing improvement.
Strong troubleshooting across distributed systems, Kubernetes, CI/CD, and live incidents.
Collaborative mindset – comfortable working across engineering, security, product, and leadership.
Comfort in a fast-paced, high-ownership environment where priorities shift but production quality doesn't.
Genuine interest in applying AI, automation, and intelligent workflows to operational work – and in building and supervising agents, not just using them.
Ownership-driven – You take responsibility for the reliability of the systems you build and operate, from SLO definition through incident command and continuous improvement.
Reliability as engineering – You treat reliability as a software problem to be solved with code, measurement, and automation – not an ops queue to be worked by hand.
This position is open to all candidates.
