Sr. Performance Engineer

Subway•Shelton, CT

18h

About The Position

The Sr. Performance Engineer owns and leads the enterprise-wide Performance Engineering function, operating as a horizontal shared service supporting all product, platform, and engineering teams across Subway's global digital ecosystem — web, mobile, kiosk, POS, loyalty, and payments. The role combines hands-on performance engineering with reliability and resilience practices and AI-native enablement to ensure scalable, performance-ready systems in accelerated delivery cycles. The Sr. Performance Engineer partners closely with Site Reliability, Observability, DevOps, and Architecture teams to improve reliability, reduce operational risk, and validate resilience through chaos engineering.

Requirements

5–7+ years in performance engineering or non-functional testing at enterprise scale.
Hands-on expertise with performance testing tools (e.g., JMeter, k6, LoadRunner, NeoLoad, OctoPerf) and observability platforms (e.g., Dynatrace, cloud-native monitoring).
Experience integrating performance validation into CI/CD pipelines and partnering with SRE/DevOps practices; familiarity with chaos engineering.
Proficiency scripting and automating in Java, JavaScript, or Python; comfortable working in cloud environments (AWS and/or Azure).
Hands-on experience with AI-assisted engineering tools, including reviewing and validating AI-generated output.
Strong communication and stakeholder leadership skills; ability to translate technical performance findings into business impact for non-technical audiences.
Bachelor's degree in Computer Science, Engineering, or a related field (or equivalent practical experience).

Nice To Haves

Experience in QSR, retail, or high-volume consumer digital commerce environments.
Familiarity with SRE principles, error budgets, and reliability-driven delivery models.
Experience with contract or consumer-driven testing practices.
Background working across mobile, kiosk, or embedded platform performance testing.

Responsibilities

Own the enterprise Performance Engineering charter as a horizontal shared service; define engagement models, intake/prioritization, and performance-readiness standards across the SDLC.
Design, script, execute, and report performance tests (load, stress, endurance, scalability) across high-volume ordering, kiosk, POS, loyalty, and payment flows; establish baselines, workload models, and SLO/SLI-aligned KPIs.
Identify and resolve bottlenecks across application, database, messaging, and infrastructure layers using observability signals (e.g., Dynatrace).
Embed automated performance validation into CI/CD pipelines (e.g., Azure DevOps) with baseline and threshold gating; standardize reporting to reduce manual effort and variability.
Partner with SRE/DevOps to define reliability-aligned targets and run controlled chaos-engineering experiments (fault/latency injection, dependency degradation) to validate resilience and recovery; feed learnings into hardened runbooks, alerts, and automation.
Define performance-readiness criteria and provide evidence-based go/no-go recommendations for releases; own escalation paths for performance risk, support production performance-incident resolution, and produce executive-level reporting.
Integrate AI-assisted workflows into performance planning, test-design acceleration, and results triage with human review; maintain AI-consumable artifacts (NFRs, workload models, baselines, thresholds) and define guardrails for safe, policy-compliant AI use.