Performance Tester

Overview We’re seeking a hands-on Performance Test Engineer to design and execute the end-to-end performance strategy for an ad-serving platform (Akka-based Java microservices) targeting <50ms response times and 4–5 million concurrent requests/users .

You’ll build the test harness, model real-world traffic, execute large-scale distributed load tests, and turn findings into actionable tuning guidance .

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).

Parameterize data, correlations, and think-time.

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 .

Technology Proficiency Needed: Load tools : Locust (Python) , JMeter ; (nice to have: k6, Gatling).

Scripting & automation : Python (core), Bash; infra spin-up via Terraform/Docker/Kubernetes for load farms.

Metrics/Tracing : CloudWatch, OpenTelemetry, Prometheus/Grafana; log analysis pipelines.

Familiarity with Java service behaviors (Maven/Gradle pipelines, JVM/GC basics); Akka concepts are a plus.

What makes you a great fit 3–5+ years in performance engineering for large-scale, low-latency distributed systems; streaming/ad-tech exposure is a plus.

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 .

Logistics Location : Remote (prefer India candidates) Schedule : Must join US morning calls (Eastern Time) as needed.

Start : 1–3 weeks from offer.

Term : Through end of January (likely extension).

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