Performance Engineer- Only W2

Saransh Inc; Vienna (VA); On-site; USD 90,000 - 120,000; Full time

Job summary

Saransh Inc. is seeking a Performance Engineer to optimize performance, scalability, and reliability for cloud-native and distributed systems.

The role requires hands-on load, stress, and endurance testing using NeoLoad, JMeter, and LoadRunner, with monitoring via Dynatrace, AppDynamics, and Splunk. The successful candidate will work with cloud deployments, microservices, Docker/Kubernetes environments, and observability practices, collaborating across technical teams to drive performance

Qualifications

• 8–10 years of experience in performance engineering.
• Hands-on with NeoLoad, JMeter, LoadRunner.
• Experience with cloud deployments and microservices.
• Experience with APM tools for root cause analysis.
• Strong communication skills and collaboration abilities.

Responsibilities

• Design and execute load, stress, and endurance tests for cloud-native/distributed systems.
• Identify bottlenecks and perform root cause analysis using APM and log analysis.
• Collaborate with engineering teams to optimize performance, scalability, and reliability.
• Implement performance engineering best practices across the organization.
• Contribute to observability improvements and resilience testing.

Skills

Performance Testing

Java

Python

SQL

Communication

Tools

NeoLoad

JMeter

LoadRunner

Dynatrace

AppDynamics

Splunk

Docker

Kubernetes

Job description

Job Description Seeking a Performance Engineer with strong expertise in performance testing, monitoring, and application scalability for cloud-native and distributed systems. The ideal candidate will have hands‑on experience designing and executing load, stress, and endurance tests using NeoLoad, JMeter, and LoadRunner, while leveraging Dynatrace, AppDynamics, and Splunk to identify performance bottlenecks and conduct root cause analysis. This role requires experience with cloud deployments, microservices, Docker/Kubernetes environments, high availability, resilience testing, and observability practices. The successful candidate will collaborate with technical teams to optimize application performance, scalability, and reliability while driving performance engineering best practices across the organization.

Job Title: Performance Engineer

Location: Onsite in Vienna, VA

Duration: 6 mos.

W2 Position

Required

• Performance Testing
• Yes
• 6 + Years
• AppDynamics Analytics
• Yes
• 6 + Years
• dynatrace
• Yes
• 6 + Years
• Kubernetes
• Yes
• 6 + Years
• NeoLoad
• Yes
• 6 + Years
• Jmeter
• Yes
• 6 + Years

Job Description

Seeking a Performance Engineer with strong expertise in performance testing, monitoring, and application scalability for cloud-native and distributed systems. The ideal candidate will have hands‑on experience designing and executing load, stress, and endurance tests using NeoLoad, JMeter, and LoadRunner, while leveraging Dynatrace, AppDynamics, and Splunk to identify performance bottlenecks and conduct root cause analysis. This role requires experience with cloud deployments, microservices, Docker/Kubernetes environments, high availability, resilience testing, and observability practices. The successful candidate will collaborate with technical teams to optimize application performance, scalability, and reliability while driving performance engineering best practices across the organization.

Responsibilities

• Professional experience as Performance Engineer with good hands‑on experience in implementing performance & high availability strategies to optimize the efficiency of applications.
• Strong hands‑on skills with test script development using Neoload, JMeter & LoadRunner. Experience in executing performance tests (load/stress/endurance) using Neoload/JMeter/LoadRunner and performance monitoring using APM tools to identify performance issues
• Hands‑on experience in APM tools like Dynatrace & AppDynamics to conduct root cause analysis for performance and scalability bottlenecks
• Able to analyze Splunk logs, Dynatrace distributed traces, Appdynamics Snapshots, method hotspots and response‑time hotspots to identify slow components and provide recommendations
• Experience in performance testing for Cloud deployments, Docker/Kubernetes containerized applications and microservices
• Strong knowledge on Java/Python, SQL query creation and manipulation skills
• Experience in Auto‑Scaling, Chaos and failover testing to measure and test for Pod/Node failures, Network exhaustion, CPU/memory saturation, Container startup failures and Dependency failures etc.
• Strong ability to track and contribute to technical discussions around application integration and high‑availability, resilience and observability
• Individual Contributor with good communication skills

• Neoload, JMeter
• Performance Testing
• Performance Monitoring using AppDynamics, Dynatrace

Years of Experience: 8-10 Years of Experience