Role: Senior Performance Test Engineer
Function: Quality Assurance / Performance Engineering
Location: Bangalore, India (Onsite)
Type: Full-time
Industry: Information Technology & Services, Computer Software, Deep Tech, Healthcare Technology
About Company
A Bengaluru-based B2B deep-tech startup founded in 2018. The company builds India's only ISO-certified autonomous testing platform.
Its flagship product is a fifth-generation AI-Augmented Autonomous Testing platform that eliminates manual scripting, achieves over 90% test coverage, and reduces testing costs by up to 80%. Ranked #27 among AI testing companies worldwide, the company serves ISVs, software services companies, and large enterprises globally.
Fully bootstrapped and led by a founder with 35+ years of product engineering experience, the team of 200 operates at the intersection of AI, deep tech R&D, and rigorous quality standards.
Position Overview
This role owns performance engineering for healthcare applications — PACS, RIS, HIS, and medical imaging systems — where reliability, speed, and regulatory compliance are non-negotiable. The engineer will design end-to-end load and scalability testing strategies, build workload models reflecting real hospital workflows, and drive observability using GCP and Datadog. Performance gaps found here directly affect clinical outcomes, making root cause precision and test coverage critical.
Role & Responsibilities
- Design and execute load, stress, endurance, spike, and scalability tests for healthcare applications including PACS, RIS, and HIS systems
- Develop and maintain JMeter, TestComplete, and Selenium scripts for APIs, web apps, and healthcare protocols (WADO-RS, WADO-URI, FHIR, DICOM REST)
- Build workload models that reflect real hospital workflows — image retrieval, order creation, reporting workflows, and viewer performance
- Perform root cause analysis for performance bottlenecks in PACS/RIS/HIS systems and document findings with remediation recommendations
- Configure Datadog APM, dashboards, alerts, and SLO tracking; correlate JMeter results with Datadog traces and logs to isolate system bottlenecks
- Use GCP services (Compute Engine, GKE, Cloud Logging, Cloud Monitoring) for test infrastructure setup, monitoring, and log analysis
- Integrate performance test suites with GitLab CI/CD pipelines and optimize infrastructure for high-throughput medical imaging workflows
Must Have Criteria
- 6–10 years of overall experience with at least 4–5 years specifically in performance testing and performance engineering
- Strong hands-on experience with Apache JMeter — script development, parameterization, distributed testing, and results analysis
- Practical, hands-on experience with Google Cloud Platform (Compute Engine, GKE, Cloud Logging, Cloud Monitoring)
- Hands-on experience with Datadog APM, log management, custom dashboards, and SLO/alert configuration
- Scripting experience with TestComplete and Selenium for web and API test automation
- Deep understanding of REST, HTTP, and microservices API protocols; experience testing FHIR, WADO-RS, or DICOM REST is required
- Working knowledge of healthcare domain systems — PACS, RIS, HIS, DICOM workflows — and HIPAA compliance basics
Nice to Have
- Hands-on experience with medical imaging viewers and image retrieval performance benchmarking
- Familiarity with IEC 62304 or other medical device software compliance standards
- Experience integrating performance tests into GitLab CI/CD pipelines
- Exposure to embedded software or regulated-environment testing workflows
- Prior experience in a product-based or ISV environment serving healthcare clients
What We Offer
- Direct ownership of performance engineering for high-stakes healthcare applications used in clinical environments globally
- Work on India's only ISO-certified autonomous testing platform, ranked #27 among AI testing companies worldwide
- Collaborative environment with a deep-tech R&D focus, led by a founder with 35+ years of product engineering experience
- Full-time onsite role in Bangalore with a 200-person team and startup-scale impact
