Principal AI & Automation Engineer
ComcastAbout the role
Job Summary
This job focuses on leading QA strategies and working with development for product excellence. It entails writing test plans and managing execution. Deep product and system knowledge is required for effective QA. The role improves testing methods and joins design reviews. Contributions to QA innovation and mentoring junior engineers are key.Job Description
*This position is unable to provide work authorization sponsorship or immigration support now or in the future.*
The Technology + Product organization works at the intersection of media and technology and our innovative teams are continually developing and delivering products and next-generation technologies that transform the customer experience.
The Comcast Network and CONNECTivity (CONNECT) organization is a highly agile, fastpaced, dedicated group at the forefront of change focused on innovating, building, and operating the best in class, most reliable access network for our customers.
About the Role:
We’re seeking a Principal AI & Automation Engineer, to lead the evolution of our next-generation quality engineering platform. This role is ideal for a highly experienced engineer who can architect intelligent, self-adaptive test automation frameworks for cloud-native, microservices-based broadband systems.
You will combine deep automation expertise, modern software architecture, and AI/ML-driven testing approaches to transform complex system requirements into scalable, resilient, and insight-driven quality solutions. As a technical leader, you will drive autonomous testing strategies, enabling faster releases, higher reliability, and continuous quality validation across DOCSIS and PON features on vCMTS ecosystem.
What You’ll Do:
- Architect and build scalable, modular, and AI-augmented test automation frameworks supporting functional, integration, and performance testing.
- Design self-healing and adaptive test systems using AI/ML techniques (e.g., anomaly detection, flaky test prediction, intelligent test selection).
- Implement shift-left and shift-right QA strategies, embedding quality across the entire SDLC and production monitoring pipelines.
- Develop data-driven and model-based testing approaches, leveraging telemetry, logs, and production data to improve test coverage and accuracy.
- Lead automation efforts for cloud-native, microservices-based DOCSIS/PON platforms, ensuring high availability and performance at scale.
- Collaborate with engineering, product, and QA teams to translate requirements into intelligent, reusable automation assets.
- Integrate QA deeply into DevOps/MLOps pipelines, enabling continuous testing, validation, and feedback loops.
- Drive Core Virtualization and network validation initiatives, applying advanced simulation, traffic modeling, and AI-assisted diagnostics.
- Build tools for predictive quality analytics, identifying risks and failure patterns before they impact production.
- Troubleshoot complex distributed systems using advanced observability, AI-assisted root cause analysis, and debugging techniques.
- Mentor engineers on modern QA practices, Python architecture, and AI-driven test automation strategies.
Skills & Experience We’re Looking For:
Required:
- Strong track record of building enterprise-grade, extensible automation frameworks.
- Strong proficiency in Linux/Ubuntu environments, CLI tooling, and automation scripting (Python, Go, Shell scripting).
- Hands-on experience with traffic generation and network test tools (e.g., IXIA, ByteBlower) and simulation platforms.
- Ability to analyze packet captures, simulate network conditions, and validate en
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