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).