Senior DevOps Engineer

AtCheck Point Software Technologies, we secure the world - and now we're securing theAI revolution. We're building aWorkforce AI Security Platform: acloud-native, multi-tenant SaaS platform that governs, protects, and enables safe AI adoption across global enterprises. This is agreenfield opportunity to help architect the infrastructure backbone of a platform that will define how organizations adopt AI at work securely.

We're looking for aSenior DevOps Engineer who owns infrastructureend-to-end, ships with confidence, and raises thereliability bar without being asked. You will work closely withbackend, full-stack, and security teams, as well asDevOps teams across other Check Point organizations, to build ahighly available, reliable, and secure production environment. If you get energized by building systems that scale, pipelines that teams love, and platforms that never sleep - this role is for you.

• Own and evolve ourcloud infrastructure acrossmulti-region production environments, end-to-end.
• Lead ourGitOps deployment model - designing and maintainingdeclarative, automated deployment workflows with zero manual gates.
• Build, maintain, and optimizeCI/CD pipelines with a strong focus ondeveloper experience, reliability, and speed.
• Initiate, implement, and champion anAI-first DevOps & SRE ecosystem - identifying opportunities, buildingAI agents and intelligent automation, and driving their adoption across engineering operations.
• Developautomation frameworks for provisioning, scaling, observability, and incident response, leveragingAI-powered tooling and agentic workflows to reduce toil.
• Operate and improve ourobservability platform: metrics, logs, alerting, dashboards,SLOs/SLIs, and on-call tooling.
• Championzero-trust secrets management andcredential-less authentication patterns across the stack.
• Partner with architects and engineering leadership oncloud cost optimization, availability, and performance.
• Build internal tooling and automation that multipliesengineering velocity across the organization.

• 5+ years of hands-on DevOps experience in aSaaS product environment - Must.
• Demonstrated initiative in applying AI to engineering operations - designing and buildingAI agents, agentic workflows, LLM-powered automation, or Model Context Protocol (MCP) integrations that reduced operational toil and improved production reliability, quality, or velocity - Must.
• Strongscripting and programming skills -Python andBash for automation, tooling, and AI agent development;Go is a plus.
• Strong motivation to continuously learn and adopt emerging technologies, and to share that knowledge across the team.
• Deep, hands-onAWS expertise;multi-cloud (AWS, GCP, Azure) experience is a strong plus - Must.
• Strong understanding ofcontainers and orchestration -Docker,Kubernetes, including workloads, networking, service mesh (Istio),Helm/Kustomize, and autoscaling (KEDA, HPA, VPA).
• Strong experience with:
  • Infrastructure-as-Code -Terraform,Crossplane, and/or cloud-native declarative tooling.
  • GitOps principles and tooling (ArgoCD or equivalent).
  • CI/CD platforms - building reusable, scalable, security-hardened pipeline templates (GitHub Actions or equivalent).
  • Secrets management - dynamic injection,IRSA/Workload Identity, avoiding long-lived credentials.
• Experience embedding security intoCI/CD:vulnerability scanning,SBOM generation, andsupply chain security (Trivy,Grype,Syft,JFrog Xray).
• Solidobservability knowledge -OpenTelemetry,Prometheus,Grafana,Datadog,ELK/OpenSearch, distributed tracing.
• Hands-on experience withAI/ML workloads or LLMOps infrastructure - a significant advantage.
• Cost-awareness (FinOps) - treating cloud spend as a core engineering metric.
• Clear communication skills - able to align engineers, security teams, and leadership around infrastructure decisions.
• A strong sense of ownership - proactively identifying gaps and driving improvements.