We are hiring a Senior / Staff QA Engineer for Fortinet's AI security product line, FortiAIGate, to own end-to-end testing of the product across both SaaS and on-premises deployments. FortiAIGate is Fortinet's security solution for the AI era, spanning the LLM Gateway, AI Guardrails, and Agent Security, and is deeply integrated with the Fortinet ecosystem (FortiOS, FortiManager, FortiClient, and more).

This role lets you work at the frontier of AI security while helping build out cloud-native SaaS test practices.

Responsibilities

Own end-to-end testing of FortiAIGate across SaaS and on-premises deployments, covering functionality, integration, performance, and reliability.
Design and implement core SaaS test capabilities: multi-tenant isolation, tenant onboarding and provisioning, metering / billing-accuracy reconciliation, and license / entitlement validation.
Validate cloud-native capabilities: elastic scaling, zero-downtime upgrades, and failover under Kubernetes deployments (single-cluster and multi-data-center).
Test the effectiveness of AI security capabilities: the LLM Gateway and AI Guardrails (Text / Policy / Image / Video & Audio) — detection accuracy, false-positive / false-negative regression — and validate protection effectiveness in collaboration with the red team.
Build and maintain automated test frameworks and regression suites; drive shift-left testing and continuous validation.
Collaborate closely with engineering (LLM Gateway / Guardrails / Agent Security / SaaS teams) and PM on test planning and release gating.

Required

Cloud / SaaS testing (must-have)
Solid software testing background, with meaningful time focused on testing SaaS / cloud-native products.
Hands-on multi-tenant SaaS testing experience: tenant isolation, provisioning, metering / billing, license, and other control-plane testing.
Familiarity with Kubernetes; able to troubleshoot independently with kubectl and comfortable with concepts such as pods, services, scaling, and rolling upgrades.
Proficiency with a performance / load-testing tool (e.g., k6, Locust, or JMeter); able to design concurrency, scaling, and high-load metering scenarios.
Strong API-level testing (Postman or scripting) and solid test automation / scripting skills (Python or equivalent).
Comfortable with observability-based troubleshooting: logs, metrics (p95/p99 latency, error rates), and distributed tracing.
AI / cybersecurity background (strongly preferred — one of the following)
Experience testing AI / LLM-related products (e.g., LLM gateways, content safety / guardrails, model-serving); or
Experience testing cybersecurity / security products (firewalls, gateways, authentication, policy engines).

This role lets you work at the frontier of AI security while helping build out cloud-native SaaS test practices.

Responsibilities

Own end-to-end testing of FortiAIGate across SaaS and on-premises deployments, covering functionality, integration, performance, and reliability.
Design and implement core SaaS test capabilities: multi-tenant isolation, tenant onboarding and provisioning, metering / billing-accuracy reconciliation, and license / entitlement validation.
Validate cloud-native capabilities: elastic scaling, zero-downtime upgrades, and failover under Kubernetes deployments (single-cluster and multi-data-center).
Test the effectiveness of AI security capabilities: the LLM Gateway and AI Guardrails (Text / Policy / Image / Video & Audio) — detection accuracy, false-positive / false-negative regression — and validate protection effectiveness in collaboration with the red team.
Build and maintain automated test frameworks and regression suites; drive shift-left testing and continuous validation.
Collaborate closely with engineering (LLM Gateway / Guardrails / Agent Security / SaaS teams) and PM on test planning and release gating.

Required

Cloud / SaaS testing (must-have)
Solid software testing background, with meaningful time focused on testing SaaS / cloud-native products.
Hands-on multi-tenant SaaS testing experience: tenant isolation, provisioning, metering / billing, license, and other control-plane testing.
Familiarity with Kubernetes; able to troubleshoot independently with kubectl and comfortable with concepts such as pods, services, scaling, and rolling upgrades.
Proficiency with a performance / load-testing tool (e.g., k6, Locust, or JMeter); able to design concurrency, scaling, and high-load metering scenarios.
Strong API-level testing (Postman or scripting) and solid test automation / scripting skills (Python or equivalent).
Comfortable with observability-based troubleshooting: logs, metrics (p95/p99 latency, error rates), and distributed tracing.
AI / cybersecurity background (strongly preferred — one of the following)
Experience testing AI / LLM-related products (e.g., LLM gateways, content safety / guardrails, model-serving); or
Experience testing cybersecurity / security products (firewalls, gateways, authentication, policy engines).

Senior Software Dev QA Specialist

Skills

Must have

Nice to have

Full description