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How much do overnight performance optimization jobs pay per hour?

As of May 29, 2026, the average hourly pay for overnight performance optimization in the United States is $17.05, according to ZipRecruiter salary data. Most workers in this role earn between $15.14 and $18.51 per hour, depending on experience, location, and employer.
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Infographic showing various Overnight Performance Optimization job openings in the United States as of May 2026, with employment types broken down into 86% Full Time, 12% Part Time, and 2% Contract. Highlights an 83% Physical, 5% Hybrid, and 12% Remote job distribution, with an average salary of $35,463 per year, or $17 per hour.

Principal Software Engineer - Performance Engineering

JPMorganChase

Jersey City, NJ • On-site

$153.30K/yr

Full-time

Posted 19 days ago


Job description

Job Summary:
JPMorganChase is one of the world's leading financial institutions, and they are seeking a Principal Software Engineer for their Payment Performance Engineering team. The role involves serving as the technical authority for performance engineering, defining non-functional requirements, and driving performance outcomes across distributed systems.
Responsibilities:
• Define and institutionalize application- and endpoint-level NFRs and SLOs, including p95/p99 latency, throughput, ramp profiles, and error budgets
• Drive proactive performance engineering through early bottleneck detection, architectural guidance, and capacity modeling
• Serve as the final technical authority for performance sign-offs across platform releases
• Design, build, and maintain automated test suites for load, stress, soak, spike, and capacity scenarios
• Virtualize partner dependencies and inject faults to validate components when upstream systems are unavailable
• Expand fully automated, environment-aware performance test execution (on-commit/overnight) with health checks and actionable sanity tests
• Build dashboards and alerts correlating performance test signals with production telemetry against defined SLOs
• Provide actionable reporting on SLO variance, drift, and per-endpoint hotspots using RUM, synthetic, and server-side metrics
• Embed performance gates into CI/CD pipelines (pre-deploy smoke, post-deploy validation, regression detection with auto-fail/notify)
• Lead chaos and resiliency experiments (CPU, memory, network, latency, dependency failures) and validate autoscaling under extreme load
• Apply AI/LLMs to workload and scenario generation, metrics interpretation, and automated reporting with measurable success guardrails
Qualifications:
Required:
• 15+ years of overall engineering experience, with 10+ years in performance engineering for high-traffic distributed systems (web, APIs, microservices, event-driven, data-centric)
• Hands-on software engineering experience with Java/Spring Boot and Kubernetes (self-managed and EKS)
• Deep expertise in workload modeling, queuing theory, and statistical analysis of latency/throughput; fluent with percentile-based SLOs and error budgets
• Proficiency with load and protocol testing tools such as JMeter and BlazeMeter
• Scripting/orchestration skills in Java, Python, or TypeScript for performance automation and execution control
• Experience with service virtualization and fault injection (e.g., WireMock, Mountebank, Toxiproxy), including record-replay and dynamic templating
• Strong observability/APM capabilities using Dynatrace and/or OpenTelemetry, plus RUM and synthetic monitoring approaches
• Experience building dashboards and analysis workflows in Kibana and/or Grafana to drive actionable decisions
• Strong CI/CD and DevOps experience (e.g., Jenkins, GitLab, GitHub Actions) including repeatable sign-offs, artifact/version alignment, and environment promotion
• Infrastructure-as-code and platform delivery experience (e.g., Terraform, CloudFormation) including autoscaling strategies
• Ability to partner across architecture, SRE, and application teams to coach standards adoption and drive release readiness
Preferred:
• Experience with data-platform performance optimization (e.g., Oracle tuning, JDBC pool tuning, Kafka throughput/partitioning, caching strategies)
• Strong systems and cloud performance background (Linux tooling, JVM tuning, containers, AWS primitives such as compute, ALB/NLB, EKS, networking)
• Experience with k6 and other modern cloud-native load testing frameworks
• Familiarity with service mesh technologies (Istio/Linkerd) and traffic-control patterns (rate limiting, backpressure)
• Practical application of LLMs for test generation, anomaly detection, or automated reporting in engineering workflows
• Experience operating in financial-services scale, low-latency systems, and/or regulated environments
• Knowledge of advanced performance tooling (e.g., perf, eBPF) and production-grade troubleshooting practices
Company:
With a history tracing its roots to 1799 in New York City, JPMorganChase is one of the world's oldest, largest, and best-known financial institutions—carrying forth the innovative spirit of our heritage firms in global operations across 100 markets. Founded in 2000, the company is headquartered in New York, USA, with a team of 10001+ employees. The company is currently Late Stage.