Senior Observability Engineer Jobs in Connecticut

At Subway, we are not standing still. We are building.

This is a business focused on what matters most: growing franchisee profitability, strengthening our brand and creating long-term value. The people who thrive here are the ones who want to make a real impact.

You will not just do the work. You will shape it.

We move fast. We think like owners. We make decisions that matter. We hold ourselves to a high standard because what we do directly impacts thousands of franchisees around the world.

If you bring energy, accountability and a bias for action, you will fit right in.

We take the work seriously, but we also know the best results come from teams that support each other, celebrate wins and show up ready to build something better every day.

This is your chance to be part of what’s next.

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.

• 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.

• 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.
• 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).

• 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.

• Mobility Allowance