QA Software Engineer NC Hybrid

Our team is part of the Cisco AI and Automation portfolio, responsible for the 'Circuit' platform - the central AI engine that powers productivity and process automation for all of Cisco. We are a rapidly expanding, high-impact group dedicated to building the vehicle for AI-driven business transformation. We operate at the intersection of applied research and production, ensuring our technology is not only cutting-edge but also optimized for performance, reliability, and functional-quality for our 80,000+ monthly users.

As an Automation QA Engineer, you are the guardian of that functional quality - owning the automated testing ecosystem that keeps Circuit reliable, scalable, and production-ready across every release. This is a hybrid position.

As an Automation QA Engineer, you will drive the transformation of our regression testing ecosystem, moving beyond manual processes to build AI-driven, fully automated test suites for both new and legacy features. You will design and own end-to-end (E2E), API, and performance test automation that ensures the Circuit platform continues to meet Cisco's high standards for functional-quality and performance.

You will build and maintain scalable test frameworks, integrate them into CI/CD pipelines for continuous quality feedback, and leverage AI-assisted coding tools (such as Cursor, Copilot, or Claude Code) to generate and maintain tests - while rigorously validating that AI-generated artifacts are stable, correct, and compliant with security standards. This is a high-visibility role where your ability to automate functional-quality and reduce technical debt directly ensures Circuit remains a reliable vehicle for process automation across Cisco.

• Architect, build, and maintain comprehensive automated regression and end-to-end test suites for the entire Circuit platform using Playwright (Type Script/JavaScript), Python/Pytest, and Selenium, replacing manual QA with scalable automation.
• Design and automate REST and GraphQL API test suites covering functional correctness, contract validation, error handling, and performance - including validation of AI/model-serving endpoints under concurrent load.
• Plan and execute load, stress, and soak tests using k6 or JMeter, track response-time percentiles (p95/p99), throughput, error rates, and AI-specific metrics such as Time to First Token (TTFT) and inter-token latency.
• Use AI agents and AI-assisted coding tools (Cursor, Copilot, Claude Code) to generate and maintain regression suites for new and legacy features; read and judge the stability of auto-generated code and ensure it does not violate security standards before it is merged.
• Develop testing approaches for AI/LLM features - validating model response quality, behavior consistency (stability testing), and end-to-end AI agent workflows across both the reasoning and action layers.
• Integrate all automated tests into CI/CD pipelines (Git Hub Actions, Jenkins, or equivalent) for continuous validation; build dashboards and reports (Grafana, Allure) and communicate quality metrics, risk assessments, and defect trends to engineering leadership.
• Act as a 'Team Captain' for automation initiatives - defining standards, mentoring peers, and collaborating with development, product, and UX teams to embed automation-first testing into the core development lifecycle.

• Bachelor's degree with 4+ years, Master's degree with 3+ years, or PhD with 1+ year of related experience in Computer Science, AI/ML, or a related technical field.
• Experience in test automation and regression framework development, with a deep understanding of functional quality assurance.
• Experience with Playwright (Type Script/JavaScript) for E2E/UI automation and/or Python with Pytest/Robot Framework; familiarity with Selenium.
• Experience with REST API testing (and familiarity with API contract testing);
  GraphQL testing a plus.
• Solid conceptual and practical knowledge of software development life cycles, including CI/CD pipelines (Git Hub Actions, Jenkins, or similar) and automated testing best practices.
• Experience in AI-assisted coding tools (e.g., Git Hub Copilot, Cursor, Claude Code), critical thinking, and Agile/Git workflows to ensure high-quality, scalable test automation

• Experience testing AI/ML-powered web applications, including LLM-based features, chatbots, or AI agent workflows.
• Hands-on experience with performance/load testing (k6, JMeter) and AI/LLM…