Hire performance QA engineers
Performance QA engineers for load, stress, scalability, and reliability testing.
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Why hire performance QA engineers from DeviQA?
DeviQA performance QA engineers define workload models and performance criteria, execute tests, analyze application and infrastructure metrics, and identify bottlenecks and capacity limits. They provide reports with evidence, risk assessments, and recommendations for optimization.
DeviQA assigns only middle and senior QA engineers to client projects.
Test leads have 8–12 years of experience managing QA teams, processes, and delivery.
DeviQA QA engineers have an average of six years of software testing experience.
All DeviQA QA engineers hold ISTQB Foundation Level certification.
Clients own all test cases, automation code, documentation, and other project IP created from the first day.
Rates, team costs, and invoicing terms are defined before the engagement begins.
Choose staff augmentation, a dedicated QA team, project-based delivery, or managed testing.
Written and spoken English proficiency is verified before an engineer joins the project.
14
DeviQA QA engineers work across 14 locations.
3+
Average employee tenure exceeds three years.
4.4%
DeviQA’s employee turnover rate is 4.4%, equivalent to approximately 96% employee retention.
3-7
Typical client projects last between three and seven years.
Core competencies of DeviQA performance QA engineers
DeviQA performance QA engineers cover workload modeling, test implementation, system monitoring, bottleneck analysis, CI/CD integration, and performance reporting.
Performance testing engineering competencies
Design and execute load, stress, spike, soak, volume, and scalability tests
Build and maintain performance test suites with JMeter, k6, Gatling, and LoadRunner
Model production-based user journeys, transaction volumes, concurrency, and traffic patterns
Identify application, database, infrastructure, API, and microservices bottlenecks
Correlate response times and throughput with CPU, memory, garbage collection, database locks, and infrastructure metrics
Integrate baseline and regression performance tests into CI/CD pipelines
Monitor test environments using Grafana, Prometheus, the ELK Stack, and Datadog
Investigate performance failures using logs, distributed traces, monitoring data, and profilers
Performance delivery and collaboration competencies
Define performance goals, workload models, test scenarios, baselines, and acceptance thresholds
Report bottlenecks, capacity limits, risks, and findings in business and technical terms
Coordinate performance investigations with Development, DevOps, database, and architecture teams
Translate test results into prioritized optimization recommendations
Align performance scenarios with critical business flows, production usage, and release scope
Maintain test reports, monitoring dashboards, scripts, workload models, and execution documentation
Track performance baselines and detect regressions across releases
DeviQA’s AI advantage
At DeviQA, we use AI to make testing smarter and simpler. Our ecosystem is built to deliver faster, smarter, and more cost-efficient results — so your team can do more in less time.
DeviQA AI ecosystem
AI-powered IDE assistant
Reduces test script writing time
QA companion
Provides suggestions for test optimization and addresses gaps
Automated code review
Flags unused variables, improper loops, and other common errors
AI for API testing in Postman
Streamlines API test case creation and response validation
Features
Test case creation
Code review
Exploratory planning
Log analysis
without AI
6 hrs
3 hrs
2 hrs
2 hrs
with DeviQA AI
4 hrs (33% saved)
2 hrs (33% saved)
45 min (60% saved)
1 hr (50% saved)
Hire performance QA engineers that help you scale without slowdowns.
Choose how to hire performance QA engineers
Dedicated performance QA team
A managed performance QA team that works exclusively on your product. DeviQA owns the agreed testing strategy, workload modeling, test implementation, execution, analysis, and reporting.
Best for:
Ownership of the agreed performance testing scope and deliverables
Planned testing capacity across release cycles
Defined test reports, dashboards, risk communication, and escalation processes
Ongoing baseline tracking and performance regression testing
Performance QA staff augmentation
Add individual performance QA engineers to your existing team. You retain control over their tasks, priorities, tools, and day-to-day work.
Best for:
Matched performance QA profiles within 48 hours
Flexible capacity based on your testing workload
Direct control over daily tasks, test scope, and priorities
Integration with your existing test environments, monitoring stack, and CI/CD workflows
Abbott Laboratories is a global healthcare giant
90%
Test coverage
1.6k+
Test cases created
X18
Faster regression testing run
Compass is the first modern real estate platform
85%
Test coverage
2k+
Test cases created
2.5x
Faster regression testing run
Arklign is a dental practice platform
95%
Test coverage
5k+
Test cases created
3k+
Number of critical bugs logged
Tipalti is a payment automation platform
12
Years of cooperation
100%
Covered performance
2x
Faster regression testing time
Xola is a booking system for tours and attractions
90%
Test coverage
3.2k+
Automation test scripts created
1-2h
Time of regression
How to hire performance QA engineers from DeviQA
Hire performance QA engineers through a four-step process—from defining your testing requirements to onboarding.
Define your performance testing needs
Share your system architecture, production traffic patterns, critical user flows, performance thresholds, monitoring stack, and release schedule.
Choose a cooperation model
Choose individual performance QA engineers managed by your team or a dedicated team managed by DeviQA within the agreed performance testing scope.
Review and interview candidates
We provide matched profiles within 48 hours. You interview the candidates and select the engineers whose technical experience and availability fit your project.
Onboard your performance QA engineers
The selected engineers join your tools and workflows, align with Development, DevOps, database, and architecture teams, and begin working on the agreed performance testing tasks.
Sample profiles of our performance QA engineers for hire
Oleksandr
Senior Performance QA Engineer
8+ years of experience
Senior Performance QA Engineer running load and stress testing for scalable systems.
SENIOR PERFORMANCE QA ENGINEER
Designed load and stress testing scenarios for microservices processing millions of daily requests
Identified and resolved CPU, memory, and DB lock bottlenecks, improving system stability by 40%
Built scalable JMeter and k6 frameworks integrated into CI/CD pipelines
Created real-world traffic models using concurrency, ramp-up, and spike patterns
Established performance SLAs for response time, throughput, and latency
PERFORMANCE TEST ENGINEER
Ran endurance tests to detect memory leaks and long-running degradation
Analyzed logs and traces using Grafana, Kibana, and Datadog
Modeled peak-hour loads for international SaaS clients
Correlated backend metrics with test results for accurate root-cause diagnostics
Built dashboards to monitor system health under load
QA ENGINEER (BACKEND & INTEGRATION)
Validated API workflows and data flows across SQL/NoSQL databases
Worked with DevOps on environment readiness and stable test data
Performed integration and regression testing for performance-sensitive services
Reproduced backend failures using logs, mocks, and controlled scenarios
Ensured clean documentation and traceability across releases
B.S. in Computer Science
ISTQB Foundation
Advanced training in performance engineering
Performance tools:
JMeter, Gatling, k6, Locust
Monitoring:
Grafana, Prometheus, Kibana, Datadog
CI/CD:
Jenkins, GitLab CI, GitHub Actions
Databases:
PostgreSQL, MySQL, Redis
Tools:
Jira, TestRail, ELK Stack
Load, stress, endurance testing
Bottleneck and root-cause analysis
Performance diagnostics using metrics & logs
Scalable framework design
Performance SLAs and reporting
Cross-team collaboration with Dev & DevOps
Dmytro
Lead Performance QA Engineer
11+ years of experience
Lead Performance QA Engineer defining performance strategy and scalability limits.
LEAD PERFORMANCE QA ENGINEER
Defined performance strategy for a payment platform serving 10M+ active users
Improved release predictability by 55% through stable performance regression pipelines
Built scalable Gatling and Locust frameworks used across multiple squads
Introduced performance baselines and alert thresholds for critical services
Led a performance team covering backend, API, caching, and DB testing
PERFORMANCE ENGINEER
Modeled real-traffic behavior across regions, devices, and concurrency patterns
Reduced latency by 30% through targeted backend and DB optimizations
Ran comparative load tests for architecture changes and refactoring
Integrated automated performance checks into CI/CD, enabling early detection
Introduced capacity planning guidelines based on historical patterns
SENIOR QA ENGINEER (SYSTEMS & BACKEND)
Validated complex data processing, messaging queues, and async flows
Performed API contract testing using OpenAPI/Swagger
Collaborated with architects on microservices design and load impact
Conducted deep log and trace analysis using ELK and New Relic
Ensured stable staging and performance environments
M.S. in Software Engineering
Certification in Performance Engineering
Courses in load modeling and observability
Performance tools:
Gatling, Locust, k6, JMeter
Monitoring:
New Relic, Datadog, Grafana, Prometheus
CI/CD:
Azure DevOps, Jenkins, GitLab CI
Databases:
MySQL, MongoDB, Snowflake
Tools:
Splunk, ELK Stack, JMeter Plugins
Performance strategy and planning
Load modeling and scalability analysis
End-to-end system performance diagnostics
CI/CD-integrated performance testing
Cross-team leadership and reporting
Release readiness and long-term performance control
Hire performance QA engineers who stop outages before they start.
