QA Engineers — Performance & Load Testing

Job Title: QA Engineers - Performance & Load Testing
Location: New York, NY
Hire Type: W2 Contract

Must Have Technical/Functional Skills

Load-test scenario design and execution across and event/websocket traffic; performance analysis (latency percentiles, error rates, throughput); bottleneck identification.

Mandatory Expectations

• Hands-on Performance & Load Testing experience is non-negotiable.
• We are seeking top-tier senior specialists, not generalist engineers.
• Deep expertise with k6 is preferred; experience with Locust, Gatling, or similar frameworks is required.
• Experience performing large-scale distributed load generation.
• Strong understanding of performance engineering principles including scalability, resiliency, throughput, latency analysis, and bottleneck identification.
• Hands-on experience with modern observability tooling including Grafana, Prometheus, Datadog, OpenTelemetry, distributed tracing, and APM platforms.
• Experience working with cloud-native, microservices-based, event-driven architectures.
• Proven ability to identify, analyze, and remediate complex performance issues across application, messaging, database, and infrastructure layers.

Technical Skills

• 7+ years of software engineering experience with strong focus on performance engineering.
• Advanced programming skills in Python, Java, Go, or Node.js.
• Proven experience building performance testing frameworks and traffic replay solutions.
• Hands-on expertise with k6, Locust, Gatling, or custom load generation frameworks.
• Strong understanding of distributed systems, event-driven architectures, and microservices.
• Experience parsing large-scale API logs, event logs, telemetry data, and production traffic exports.
• Experience with Kafka, Google Pub/Sub, WebSockets, REST APIs, gRPC, and streaming platforms.
• Knowledge of distributed load generation methodologies and performance engineering best practices.
• Familiarity with cloud-native platforms and Kubernetes environments.
• Strong experience with observability tools including Grafana, Prometheus, Datadog, OpenTelemetry, and distributed tracing platforms.
• Experience leveraging AI/LLM-assisted techniques to generate realistic performance test scenarios.

Functional Skills

• Performance engineering and application optimization.
• Tool and framework development.
• Performance problem diagnosis and remediation support.
• Scalability analysis and workload simulation.
• Strong analytical and troubleshooting skills.
• Collaboration across QA, Infrastructure, and Product Engineering teams.
• Technical documentation and communication.

Roles & Responsibilities

• Design and build traffic replay tooling for large-scale transactional workloads.
• Convert API logs, event streams, and production exports into realistic, replayable load test scenarios.
• Develop custom utilities and frameworks to support large-volume performance testing.
• Simulate real-world user behavior and workload patterns across distributed systems.
• Support execution of large-scale load, stress, and scalability testing activities.
• Analyze application behavior, resource utilization, and bottlenecks under load.
• Partner with QA and Infrastructure Engineers to design end-to-end performance testing strategies.
• Support performance remediation efforts through detailed analysis and tooling enhancements.
• Enable automated performance testing within CI/CD workflows.
• Drive continuous improvements in platform performance, scalability, and reliability.