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Remote role, metro location, and broad skillset requirements increase applicant competition.
Requires deep cloud-native performance and distributed-systems expertise, reducing cross-industry transferability.
Explicit 8+ years plus mandatory performance, Kubernetes, and language expertise makes shortlisting highly strict.
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Architect and scale automated performance testing frameworks for a distributed, multi-cluster cloud control plane.
Own test strategy for Anywhere Cloud validating Zero-Trust security, API contracts, and cross-cluster resource management under load.
Profile performance bottlenecks, optimize architectures, and mentor junior/mid-level test engineers on distributed systems performance.
8+ years professional experience in Software in Test (SDET), Performance Engineering, or Quality Engineering with leadership (Staff/Lead Engineer) roles.
Expertise in custom load generation and industry tools (JMeter, Gatling, Locust, k6) for REST, gRPC, and database performance testing.
Deep hands-on experience with Kubernetes scaling, Service Mesh overhead evaluation, and benchmarking storage IOPS (Ceph, S3).
Expert-level programming skills in Go, Python, or Java for building performance frameworks and custom Kubernetes operators.
Experienced in building large-scale performance testing frameworks for distributed cloud-native platforms with leadership accountability.
Strong domain expertise in compute/streaming engines (Spark, Kafka, Flink) and Lakehouse scale, including Apache Iceberg.
Proficient in observability and profiling tools (Prometheus, Grafana, OpenTelemetry) to monitor latency and resource bottlenecks during soak tests.