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Infrastructure, Tools and AI Engineering Manager
Not specifiedFull-timeEngineering ManagementElectronics Manufacturing
Lead an infrastructure and tooling engineering team supporting the full development lifecycle of a network operating system. Own scalable development, integration, testing, CI, and AI-assisted quality capabilities.
Responsibilities
- Lead and mentor infrastructure and tooling engineers while setting priorities and technical direction.
- Design, build, and maintain scalable development, integration, and test infrastructure for a network operating system.
- Develop LLM-based tools for failure classification, root-cause clustering, anomaly detection, and test-flakiness prediction.
- Reduce regression runtime through parallelization, intelligent test selection, and dependency-aware scheduling.
- Develop expertise in network operating system architecture, including subsystem design, hardware abstraction, and management planes.
Requirements
- Bachelor’s degree in engineering, computer science, or a related field, or equivalent experience.
- At least 8 years of software engineering experience, including 3 years leading or managing software development teams.
- Experience hiring, mentoring, setting technical direction, creating roadmaps, and influencing across teams.
- Experience developing software testing tools and test infrastructure.
- Strong Python skills and experience building production-quality automation frameworks and tooling.
- Experience designing and operating CI/CD systems at scale, such as Jenkins, GitLab CI, or GitHub Actions.
- Hands-on experience building, integrating, or productizing LLM or AI-assisted developer tooling.
- Strong analytical and problem-solving skills with a data-driven approach.
Nice to have
- Deep Linux expertise, including system internals, networking, process management, and scripting.
- Experience with LLM-powered test analysis or AI-enhanced DevOps tooling in production.
- Knowledge of Ethernet switching, L2/L3 protocols, QoS, VLANs, and high-performance data-center networking.
- Experience with code-coverage instrumentation in large C/Python codebases and test prioritization.
- A record of improving regression runtime, test reliability, or CI throughput in embedded or systems software environments.