SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Tigera is hiring a QA Engineer to own quality end-to-end for Lynx, a new product that detects and governs AI agents in Kubernetes environments at runtime. You'll be embedded with a small, high-autonomy engineering team focused on shipping fast without compromising the trust customers place in a security product.
In this hands-on role, you'll treat quality as engineering rather than gatekeeping. Responsibilities include owning the complete test strategy across unit, integration, end-to-end, and non-functional testing; designing and building automated test suites and CI pipelines that provide fast, trustworthy signal on every change; and testing distributed, Kubernetes-native systems under realistic load and failure conditions.
A key aspect of this role is developing approaches for validating ML-driven behavior—detections, risk scores, and behavioral baselines—including regression testing, ground-truth datasets, and evaluation of false-positive/false-negative rates. You'll build tooling, fixtures, and synthetic data that let the team reproduce agent behavior and edge cases reliably, investigate and isolate defects, and serve as the quality voice in design and release decisions.
You bring 5+ years in software QA or test engineering with a strong bias toward automation. You're proficient in at least one programming language (Python preferred), have hands-on experience testing distributed systems and APIs, and are comfortable with containers and Docker. You've built and maintained CI/CD pipelines, have strong debugging instincts, and communicate clearly in writing and verbally.
Nice-to-have skills include experience testing AI-powered applications or AI/ML systems, working knowledge of Kubernetes, familiarity with observability and telemetry pipelines, experience validating ML or data-driven systems, performance/load/chaos testing, exposure to eBPF or runtime security tooling, and open-source contributions to testing frameworks.
