Location: Hybrid - KL, Malaysia 

Core Responsibilities

• Architect and oversee sophisticated performance testing frameworks that span distributed systems, APIs, SDKs, and various service integrations across the organization.

• Plan, run, and evaluate performance, load, soak, and stress testing scenarios that mirror real-world traffic volumes, concurrency levels, and usage patterns.

• Develop scalable, reusable performance testing infrastructures using tools like JMeter, k6, Gatling, Locust, or LoadRunner Enterprise, and ensure seamless integration into CI/CD pipelines.

• Create and continually refine the Performance Testing Runbook — a comprehensive guide detailing environment configuration, load profiles, KPIs, execution standards, and performance sign-off requirements.

• Implement robust observability by instrumenting systems with APM and monitoring platforms (Datadog, New Relic, Grafana, Prometheus, ELK, OpenTelemetry) to align test outcomes with backend telemetry data.

• Execute in-depth root-cause and bottleneck analyses across the full technology stack — including network, API layers, caching mechanisms, databases, and compute resources — to identify performance constraints and improvement opportunities.

• Work closely with backend engineers, DevOps, and SRE teams to evaluate system capacity, investigate regressions, validate tuning experiments, and forecast performance trends.

• Automate the collection and enforcement of performance metrics within CI/CD pipelines, supporting objective release decisions through data-driven gating and clear, visualized performance trends.

• Provide guidance, mentoring, and technical leadership to QA, automation, and infrastructure teams to elevate the overall maturity of performance engineering across the company.

Required Technical Skills & Expertise 

• Minimum 8 years of practical experience conducting performance, load, and scalability testing for complex, high-volume or enterprise-grade systems.

• Deep hands-on knowledge of a variety of performance testing tools such as JMeter, k6, Gatling, Locust, LoadRunner Enterprise, NeoLoad, or BlazeMeter.

• Strong scripting and automation capabilities in languages like Python, JavaScript/TypeScript, or Groovy.

• Solid understanding of distributed system design, including microservices architectures, API-driven systems, message queues, asynchronous workflows, and event-based processing.

• Proficiency with profiling and diagnostic utilities such as YourKit, JProfiler, VisualVM, Chrome DevTools, perf, and flame graphs.

• Ability to analyze and interpret data from APM platforms (Datadog, New Relic, Dynatrace, AppDynamics) and system monitoring tools (Grafana, Prometheus, CloudWatch).

• Strong foundation in networking and infrastructure concepts: TCP/IP, HTTP/2, caching models, CDN behavior, load balancing techniques, and service mesh patterns.

• Experience defining SLAs, SLOs, and performance benchmarks, and integrating them into CI/CD workflows as enforceable quality gates.

• Excellent analytical skills with the ability to distill high-volume telemetry into actionable insights, meaningful stories, and accurate capacity predictions.

• Confident working with Git-based workflows and CI/CD platforms such as Jenkins, GitHub Actions, GitLab CI, or CircleCI.

Preferred / Bonus Qualifications 

• Experience executing performance testing within cloud-native or containerized environments (Kubernetes, Docker, AWS Fargate, GCP GKE).

• Knowledge of chaos engineering or resilience testing tools like Gremlin, Litmus, or ChaosMesh.

• Familiarity with database query optimization and performance tuning for PostgreSQL, MySQL, Redis, or MongoDB.

• Understanding of API gateway performance patterns (Kong, NGINX, AWS API Gateway).

• Background in designing, maintaining, or evolving enterprise-scale performance testing frameworks or internal test platforms.

• Contributions to internal or open-source performance engineering playbooks, guidelines, or tooling.

What Success Looks Like 

• A Performance Testing Runbook that becomes the definitive reference for all future load, stress, and scalability assessments across the organization.

• Fully automated performance baselines integrated into build and release pipelines, providing continuous insights.

• Clear, organization-wide visibility into bottlenecks, regression trends, capacity thresholds, and system hotspots.

• A mature, data-driven performance culture where every release is validated, measured, and continuously optimized.

• Actionable, evidence-backed recommendations that directly enhance system architecture, product reliability, and engineering quality.

Benefits 

Work Tools

• High-performance Mac workstations plus any additional equipment needed to maximize productivity.

• Collaboration tools including Google Workspace (Chat, Gmail, Drive), Confluence, Jira, and GitLab.

Professional Development

• Access to advanced training programs and industry conferences.

• A strong internal culture of knowledge sharing and cross-team learning.

Additional Perks

• Comprehensive medical, dental, and optical insurance coverage for employees and their dependents.

• Flexible working hours tailored to individual schedules and team needs.

• No formal dress code.

• A modern, comfortable office environment designed for focused and collaborative work.