Senior Associate - Performance / Quality Engineering Lead

New York Life Insurance Co•Remote, any

1d•$111,500 - $159,000•Hybrid

About The Position

This role acts as the enterprise owner and governor of performance engineering platforms, observability tooling, and non-functional quality standards across business-critical platforms, including AI-enabled systems. Operating within a Center for Enablement (C4E) model, this role enables multiple value streams through standardized performance practices, governed tooling, reusable assets, and metrics-driven insights. This role owns the end-to-end performance engineering capability—from strategy and standards to tooling administration, CI/CD integration, and observability-driven diagnostics. You will partner closely with Engineering, DevOps, SRE, Cloud, and Architecture teams to embed performance, scalability, reliability, and resiliency early and continuously across the SDLC. This is a platform ownership and enablement-led leadership role, combining tooling administration, observability governance, and hands-on performance engineering expertise.

Requirements

Enterprise owner and governor of performance engineering platforms
Experience with observability tooling
Knowledge of non-functional quality standards across business-critical platforms, including AI-enabled systems
Experience operating within a Center for Enablement (C4E) model
Ability to enable multiple value streams through standardized performance practices, governed tooling, reusable assets, and metrics-driven insights
Ownership of end-to-end performance engineering capability—from strategy and standards to tooling administration, CI/CD integration, and observability-driven diagnostics
Partnership with Engineering, DevOps, SRE, Cloud, and Architecture teams to embed performance, scalability, reliability, and resiliency early and continuously across the SDLC
Platform ownership and enablement-led leadership
Tooling administration, observability governance, and hands-on performance engineering expertise
Experience with performance testing platforms including NeoLoad, LoadRunner / Performance Center, and Apache JMeter
Experience with CI/CD pipelines (Jenkins, GitHub Actions, GitLab CI, Azure DevOps)
Experience with cloud-native and distributed platforms across AWS and Google Cloud
Experience with Kubernetes/OpenShift platforms and microservices, API, and messaging architectures
Experience with observability and diagnostics platforms including Dynatrace, AppDynamics, Splunk, and Prometheus/Grafana
Experience defining enterprise standards for performance metrics, logs, traces, and correlation of test results with runtime behavior
Experience leading end-to-end root cause analysis (RCA)

Responsibilities

Define and govern enterprise performance engineering standards across load, stress, spike, endurance, soak, capacity, and resiliency testing
Own performance-related non-functional requirements (NFRs) and acceptance criteria in partnership with Architecture and Engineering
Drive proactive performance engineering through early bottleneck identification, workload modeling, capacity planning, and scalability/reliability design guidance
Embed shift-left performance validation within Agile SDLCs and continuous delivery pipelines
Enable teams via standardized frameworks, reusable assets, and playbooks, aligned with a C4E model, and act as an enterprise performance mentor and authority
Serve as enterprise owner and administrator of performance testing platforms including NeoLoad, LoadRunner / Performance Center, and Apache JMeter
Define and enforce tooling standards covering test design, execution models, reusability, dataset management, and environment readiness
Build, govern, and automate reusable performance test suites for scalable execution
Integrate performance testing into CI/CD pipelines (Jenkins, GitHub Actions, GitLab CI, Azure DevOps) with automated gating
Define and enforce performance baselines, thresholds, SLAs, SLOs, and release gating criteria
Govern production-like performance environments and execution strategies
Govern performance validation for cloud-native and distributed platforms across AWS and Google Cloud
Define performance standards for Kubernetes/OpenShift platforms and microservices, API, and messaging architectures
Validate elasticity, auto-scaling, failover, and resiliency under high and extreme load conditions
Support performance assurance for SaaS platforms, accounting for shared infrastructure and vendor constraints
Own and govern enterprise observability and diagnostics platforms including Dynatrace, AppDynamics, Splunk, and Prometheus/Grafana
Define enterprise standards for performance metrics, logs, traces, and correlation of test results with runtime behavior
Lead end-to-end root cause analysis (RCA) across application, JVM, container, infrastructure, and network layers
Establish and track enterprise performance KPIs including response time, latency, throughput, concurrency, error rates, and resource utilization