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Salary
$22k – $55k per year (Estimated)
Location
In office (Hyderabad)
Overview
Company
Impact
Profile match
JPMorganChase is the largest bank in the United States by assets and one of the most systemically important financial institutions in the world, with a lineage running back through more than a thousand predecessor firms to the 1799 founding of the Bank of the Manhattan Company. It combines a dominant investment bank and markets business with Chase, the largest retail banking franchise in America, plus commercial banking and asset and wealth management. Headquartered in New York, the group is unusual among banks for the scale of its technology spending, running one of the largest engineering organisations of any financial institution and deploying its own internal AI platform across the firm.

We have an exciting and rewarding opportunity for you to take your performance engineering career to the next level.

As a Software Engineer III - Performance Engineer at JPMorganChase within the Consumer & Community Banking under product line Technology, you will ensure applications are scalable, resilient, and performant. You will design and execute performance engineering solutions, identify and mitigate bottlenecks, automate testing and observability processes, and provide actionable insights that improve application reliability and customer experience. You will work across multiple technology domains and business functions to support the firm's strategic objectives through robust performance engineering practices.

Job Responsibilities

  • Design, develop, execute, and analyze performance, load, stress, endurance, and capacity tests for complex enterprise applications.
  • Identify, troubleshoot, and resolve application, infrastructure, database, and network performance bottlenecks using monitoring and profiling tools.
  • Create secure, scalable, and reusable automation frameworks for performance testing, production analytics, and monitoring.
  • Leverage enterprise-authorized AI-assisted engineering tools to improve test automation, performance analysis, documentation, and delivery efficiency while validating outputs through engineering best practices.
  • Develop and maintain performance test scripts for web, API, mobile, and distributed systems using industry-standard performance testing tools.
  • Build and enhance observability dashboards, monitoring solutions, and production analytics capabilities using tools such as Dynatrace, Splunk, Grafana, and related platforms.
  • Automate performance testing execution through CI/CD pipelines and integrate performance validation into software delivery processes.
  • Analyze production and non-production performance metrics to proactively identify trends, anomalies, capacity risks, and optimization opportunities.
  • Collaborate with software engineers, architects, SRE teams, and business stakeholders to define performance objectives and ensure performance readiness for releases.
  • Produce performance engineering reports, architecture recommendations, and capacity planning insights to support strategic technology decisions.

Required Qualifications, Capabilities, and Skills

  • Formal training or certification on software engineering, performance engineering, or related technical disciplines and 3+ years of applied experience.
  • Hands-on experience in performance engineering, system scalability testing, performance analysis, and operational stability.
  • Strong experience with performance testing tools such as JMeter, LoadRunner, BlazeMeter, NeoLoad, Gatling, WebPageTest, Puppeteer, Sitespeed.io, or equivalent technologies.
  • Experience working with observability and monitoring platforms including Dynatrace, Splunk, Grafana, ELK Stack, AppDynamics, or equivalent tools.
  • Hands-on experience integrating performance testing and monitoring processes into CI/CD pipelines using Jenkins or similar DevOps platforms.
  • Strong understanding of application architecture, distributed systems, API performance, database performance tuning, and cloud-native applications.
  • Experience using enterprise-authorized AI-assisted engineering tools to accelerate testing, troubleshooting, analysis, and documentation activities while ensuring quality and security standards.
  • Solid understanding of Software Development Life Cycle (SDLC), Agile methodologies, Application Resiliency, Site Reliability principles, and Security best practices.
  • Experience conducting root cause analysis, application profiling, memory analysis, and production issue troubleshooting.

Preferred Qualifications, Capabilities, and Skills

  • Experience with AWS, Azure, Kubernetes, containerized platforms, and cloud-based load generation environments.
  • Experience building production analytics, capacity forecasting, and performance observability solutions.
  • Knowledge of statistical techniques for workload prediction and capacity planning.
  • Experience with financial services, banking applications, or large-scale enterprise platforms.
  • Familiarity with modern observability, AIOps, and performance engineering practices.
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