Senior Cloud Security Engineer
Owns cloud security end to end for Placer.ai's large-scale location-analytics data platform: securing GCP and Kubernetes environments, building policy-as-code guardrails, managing secrets, driving vulnerability management and incident response, and embedding security into CI/CD alongside the infrastructure team.
- Compensation
- Not disclosed
- Location
- Ramat Gan, Israel
- Work setup
- Not specified
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 3+ years
- Category
- Security
- Posted
Skills
Must have
- 8+ years of hands-on experience in security, infrastructure or DevOps engineering, including significant cloud security ownership in production
- Deep hands-on experience securing a public cloud environment (GCP strongly preferred; AWS or Azure considered)
- Production Kubernetes security experience: RBAC, network policies, admission control and workload hardening
- Strong Terraform (or similar) and Python or Go skills, with a track record of building security automation beyond off-the-shelf tools
- Sound judgment in prioritizing risk: knows when to block, when to guide and when to accept
- Uses AI to scale security work in practice, e.g. LLM-assisted triage, generating and testing policy-as-code, or automating design reviews
- Familiar with the security risks of LLM APIs and AI services in production, or eager to build that expertise
Nice to have
- Application security or DevSecOps experience
- Experience securing data platforms and enforcing data access governance
- A background in DevOps, SRE or Platform engineering before moving into security
Full description
SUMMARY:
We’re looking for a Senior Cloud Security Engineer to own the security of a large-scale data platform that processes billions of events for thousands of customers, where privacy is a core product commitment.
You’ll own cloud security end to end, building the guardrails, automation and controls that make the secure path the default for every engineer. You’ll work closely with the infrastructure team who own the platform, and see your decisions go straight to production.
RESPONSIBILITIES:
- Own the security posture of our GCP and Kubernetes environments: IAM, network segmentation, workload hardening, and data access to BigQuery, Bigtable and other data stores, detecting and fixing cloud misconfigurations continuously and automating remediation wherever possible
- Build secure-by-default foundations: hardened base images, secure Kubernetes configurations, and policy-as-code guardrails for Kubernetes and Terraform
- Partner with engineering to embed security into CI/CD, with automated fixes and alerts instead of manual checklists
- Own secrets and key management end to end, including rollout, rotation and access policy
- Drive vulnerability management from discovery to fix, prioritizing by real exposure
- Review new services and designs with practical, lightweight threat modeling
- Lead security incidents from containment to post-mortem
- Serve as the go-to security expert across R&D, mentoring engineers and helping teams adopt AI services safely
REQUIREMENTS:
- 6+ years in security, infrastructure, DevOps, or SRE, including 3+ years owning cloud security in production
- Deep hands-on experience securing a major public cloud. We run on GCP; strong AWS or Azure engineers ramp quickly here.
- Production Kubernetes security: RBAC, network policies, admission control, workload hardening
- Terraform (or similar) plus Python or Go. You’ve built security automation, not just configured off-the-shelf tools.
- Sound judgment on risk: you know when to block, when to guide, and when to accept
AI FLUENCY & ENGINEERING EXCELLENCE:
- Uses AI to scale security work in practice, e.g. LLM-assisted triage, generating and testing policy-as-code, or automating design reviews
- Familiar with the security risks of LLM APIs and AI services in production, or eager to build that expertise
NICE TO HAVE:
- Application security or DevSecOps experience
- Experience securing data platforms and enforcing data access governance