Performance Test Engineer - Ad-Serving Platform
Remote (prefer India candidates), US morning calls (Eastern Time)ContractMiddle
Salary not disclosed
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Job Details
- Experience
- 3–5+ years
- Required Skills
- DockerPythonBashJavaJMeterJVMKubernetesGrafanaMavenPrometheusTerraform
Requirements
- 3–5+ years in performance engineering for large-scale, low-latency distributed systems
- Demonstrated success hitting strict SLAs (p95/p99 latency) under millions of users/RPS
- Strong Python and test-automation skills
- Ability to build maintainable, reusable test frameworks
- Experience designing realistic workload models, synthetic data generation, and distributed load execution in cloud
- Analytical, communicates crisply with stakeholders, converts data into prioritized recommendations
- Proficiency with Locust (Python) and JMeter
- Experience with scripting & automation using Python (core) and Bash
- Experience with infra spin-up via Terraform/Docker/Kubernetes for load farms
- Proficiency with metrics/tracing tools: CloudWatch, OpenTelemetry, Prometheus/Grafana; log analysis pipelines
- Familiarity with Java service behaviors (Maven/Gradle pipelines, JVM/GC basics)
- Akka concepts are a plus
Responsibilities
- Own the performance test strategy & plan (load, stress, spike, soak, scalability, failover)
- Model traffic for ad-supported streaming (burstiness, fan-out, cache hit/miss, cold-start, geo distribution, p95/p99/p999)
- Build automated load frameworks & scripts (preferably Locust/Python; JMeter where appropriate)
- Orchestrate distributed load generation (cloud workers, containerized runners) to simulate 4–5M concurrent at scale
- Integrate with observability/APM (metrics, logs, traces) to correlate system bottlenecks across app, JVM/GC, Akka dispatchers, network, caches, and databases
- Produce capacity models & SLAs/SLOs dashboards; run performance gates in CI/CD
- Partner with DevOps & developers to recommend tuning (thread pools, connection pools, GC, autoscaling, cache strategies, DB indexes/queries)
- Document test design, scenarios, results, and clear remediation plans
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