Software Engineers

Software Engineers — Performance & Load Testing

Must Have Technical/Functional Skills

We are seeking highly skilled Software Engineers with deep expertise in performance engineering and workload simulation. This role will focus on building traffic replay solutions, converting production data into realistic test scenarios, and supporting large-scale performance validation efforts for a high-volume event-driven platform.

Hands-on performance and load testing experience is essential. We are seeking senior specialists, not generalist software engineers. Familiarity with tools such as k6 (preferred), Locust, Gatling, distributed load generation, and modern observability stacks is required.

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.

Salary Range- $100,000-$120,000 a year