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Wiz is a fast-growing cloud security platform trusted by over 65% of the Fortune 100. As a Solutions Support Engineer, you'll be part of a global technical support team delivering expert-level troubleshooting across Wiz's cloud-native security platform.
You'll investigate complex, multi-domain technical issues spanning cloud infrastructure, workload protection, vulnerability management, and runtime defense across AWS, Azure, GCP, and OCI environments. Your responsibilities include:
- Investigating and resolving customer technical issues across cloud security posture management, vulnerability scanning, threat detection, container/Kubernetes security, identity & access management, network analysis, and data security
- Troubleshooting cloud connector and integration failures, including IAM/permissions issues, network connectivity, API authentication, and scanning infrastructure
- Diagnosing workload scanning and runtime security issues such as outpost deployment, sensor configuration, registry scanning, malware detection, and file integrity monitoring
- Analyzing vulnerability findings, triaging false positives, validating detection accuracy, and assessing SBOM/SCA results
- Supporting shift-left security workflows including CI/CD scanning, IaC security, admission controllers, and Kubernetes connectors
- Designing and implementing automation to scale support operations using AI agents and agentic workflows to improve triage accuracy and resolution efficiency
- Participating in on-call rotation for after-hours, holiday, and weekend support coverage
Required qualifications: 5+ years of hands-on technical experience in customer support, technical support, system administration, or related customer-facing role; 2+ years working with cloud platforms (AWS, Azure, GCP) including IAM, networking, and core services; 1+ years deploying and troubleshooting production Kubernetes clusters; strong understanding of cloud security fundamentals; experience reading and debugging code in Python, Shell, JavaScript/JSON, Java, Go, or Terraform/HCL; proficiency with command-line tools and Linux; familiarity with current AI landscape including LLM architectures.
Nice-to-have skills include vulnerability management experience, threat detection/runtime security background, agentic workflows/RAG architecture experience, Infrastructure-as-Code expertise, CI/CD pipeline knowledge, GraphQL/REST API debugging, and compliance framework familiarity (CIS, NIST, SOC2, PCI-DSS, HIPAA).
