Senior Performance SDET (on-site)

Ziosk•Plano, TX

28d•Onsite

About The Position

Welcome to Ziosk, where we empower restaurants to focus on what matters most: the guest experience! Have you ever used a tablet to pay at a restaurant? We pioneered the pay-at-the-table concept and we’re cooking up a plan to transform the restaurant industry. Our recipe for success has been adapting and growing to exceed the needs of our clients, such as Olive Garden, Texas Roadhouse, Chili’s and more – helping them create an experience that keeps guests coming back. Today we have a full menu of solutions, from hardware to software to cloud-based and AI driven products, all focused on helping them create the best guest experience possible to grow their bottom line. Our secret sauce? Our people! Every day, they’re cooking up bold solutions, making Ziosk the leading pay-at-the-table provider in the industry. Want a seat at our table? The Senior Performance SDET establishes and scales AI-driven performance testing as a core engineering capability at Ziosk. This role owns performance frameworks, tooling, standards, reporting, and release quality gates to ensure systems remain scalable, reliable, and responsive under real-world operating conditions. This is a hands-on engineering role that blends test automation, performance analysis, coding, coaching, and practical testing leadership. The Senior Performance SDET partners with Engineering, Product Owners, Solutions Engineering, IT, and testing teams to identify risks early, validate system behavior under load, and help teams build better quality into their work. The role is expected to use AI assistants, agents, and automation to accelerate test creation, analysis, investigation, and decision support while applying sound engineering judgment to validate results.

Requirements

7+ years of experience in software development, SDET, performance testing, software quality, or related engineering disciplines.
3+ years of hands-on performance testing experience, including load, stress, scalability, and reliability validation.
Experience building automated performance testing frameworks and integrating tests into CI/CD workflows.
Strong experience with Gatling, JMeter, k6, Locust, or similar performance testing platforms.
Strong understanding of APIs, distributed systems, integrations, cloud-connected applications, and transaction-heavy systems.
Experience analyzing telemetry, logs, monitoring data, performance metrics, and system behavior to identify root causes.
Strong programming or scripting skills in Java, Kotlin, JavaScript, TypeScript, Python, C#, or similar languages.
Experience using AI-assisted development or testing tools to improve engineering effectiveness.
Strong communication and collaboration skills, with the ability to explain technical findings to engineering and business stakeholders.
Candidates must be eligible to work in the U.S. and be able to commute daily to Plano, TX.

Nice To Haves

Experience with Gatling Enterprise.
Experience building AI-assisted testing, analysis, reporting, or engineering automation workflows.
Experience creating or using AI agents to automate repetitive engineering activities.
Experience testing payment systems, high-volume customer-facing applications, or device-integrated solutions.
Experience with observability platforms such as Grafana, Application Insights, Kibana, Elasticsearch, Prometheus, Datadog, or similar tools.

Responsibilities

Own the performance testing strategy, standards, and reusable practices across Ziosk products and platforms.
Define performance objectives, scalability targets, baselines, and release quality gates for key initiatives.
Drive shift-left performance practices so teams address scalability and reliability risks early.
Partner with Engineering, Product Owners, and testing teams to turn performance data into clear risk decisions.
Design, build, and maintain automated performance testing frameworks using Gatling Enterprise and supporting tools.
Create reusable simulations, test data, load models, and automation assets for APIs, services, and integrated systems.
Integrate performance tests, quality gates, reporting, and trend analysis into Azure DevOps pipelines and release workflows.
Use AI tools and agents to accelerate test design, maintenance, optimization, reporting, and coverage expansion.
Design and execute load, stress, endurance, spike, capacity, and scalability tests using realistic usage patterns.
Analyze application, API, database, infrastructure, telemetry, logs, and monitoring data to explain performance behavior.
Investigate latency, throughput, resource utilization, scalability, degradation, and reliability concerns.
Use AI-assisted analysis to identify trends, anomalies, bottlenecks, likely root causes, and recommended next actions.
Build dashboards, scorecards, KPIs, and decision-support reporting that connect technical performance to business impact.
Validate AI-generated findings through evidence-based analysis and partner with teams to confirm improvements.
Serve as a subject matter expert for performance testing, performance quality, and AI-assisted performance engineering.
Mentor engineers and testers on performance methods, tooling, automation, hands-on testing, and AI-enabled workflows.
Create reusable prompts, agents, workflows, examples, and accelerators that improve team productivity and consistency.
Promote responsible AI adoption while helping teams improve the way they test, analyze, and release software.