The 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 the company.

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, and 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 and support production performance-incident resolution; 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