Staff Software Development Engineer in Test - Performance Focus

Responsibilities

• Design and build an agentic, AI-first self-service performance platform for developers.
• Build reusable tools, templates, SDKs, commands, and workflows for API, UI, service, and code performance testing.
• Integrate performance checks into CI/CD pipelines and developer workflows.
• Build AI-assisted workflows for: performance risk assessment, test creation, test execution, result analysis, root cause grouping, Jira defect creation, service-team notification.
• Support performance validation for Critical User Journeys, high-risk releases, and scale events.
• Standardise performance test inputs, outputs, thresholds, evidence, and reporting.
• Integrate with observability systems such as Datadog, logs, traces, dashboards, and reporting tools.
• Partner with product engineering, SRE, platform, QA, and architecture teams.
• Mentor engineers and help teams adopt self-service performance practices.

Requirements

• 10+ years of professional software engineering experience.
• 5+ years building developer platforms, frameworks, internal tools, CI/CD systems, performance tooling, or cloud-native automation.
• Strong software engineering experience in Python, TypeScript/JavaScript, Go, or similar languages .
• Experience building developer platforms, frameworks, internal tools, automation, or CI/CD systems.
• Strong understanding of APIs, distributed systems, cloud services, and service-to-service interactions.
• Experience with performance testing concepts such as load, spike, soak, stress, capacity, and regression testing.
• Experience with observability using metrics, logs, traces, dashboards, and alerts.
• Ability to design simple, reusable workflows that developers can adopt easily.
• Strong cross-functional communication and technical leadership.
• Experience with tools such as k6, Locust, JMeter, Gatling, Playwright, or Web Vitals .
• Experience with Datadog, OpenTelemetry, Grafana, Prometheus, or InfluxDB .
• Experience with Kubernetes, cloud-native systems, or large-scale SaaS platforms.
• Experience with SLOs, SLIs, Apdex, error budgets, or burn-rate alerting.
• Experience building AI agents, MCPs, AI-assisted developer tools, or agentic automation workflows.
• Experience with Jira automation, defect routing, or engineering dashboards.
• What Success Looks Like
• Developers can create and run performance tests with minimal manual support.
• Performance checks are part of normal development and CI/CD workflows.
• AI-assisted workflows help teams generate tests, analyze failures, and create actionable defects.
• Performance results are consistent, observable, and easy to act on.
• Product teams can detect regressions earlier and improve service performance faster.
• Why This Role Matters
• Performance is critical to customer trust. This role will help Alteryx move from manual, centralized performance testing to a scalable, AI-first, self-service performance engineering model used across engineering teams
• This position involves access to software/technology that is subject to U.S. export controls. Any job offer made will be contingent upon the applicant's capacity to serve in compliance with U.S. export controls.

Additional Information

Meet the Moment with Alteryx We're living through a once-in-a-generation shift in how work gets done. Data, automation, and AI are quickly becoming the center of every business decision - and Alteryx is leading the transformation. You'll be working on the challenges that sit at the heart of modern business. No matter your role, the work you do will help organizations move faster, see more clearly, and tackle questions that used to feel impossible. If you're ready to meet the moment with innovation, curiosity, and excellence, there's a place for you here. We are hiring a Staff Software Engineer to build Alteryx's next-generation Performance Engineering Platform. This role is for a strong software engineer with 10+ years of software engineering experience, including 5+ years building developer platforms, performance tooling, CI/CD systems, or cloud-native automation. The goal is to help engineering teams test, understand, and improve performance earlier in the SDLC through developer-first, AI-assisted tooling. This is not a traditional performance testing or QA execution role. This is a platform engineering role focused on frameworks, automation, observability, CI/CD integration, and agentic AI workflows.

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