Senior Network Automation Engineer, Network Infrastructure and Capacity
Role details
Job location
Tech stack
Job description
- Design, develop, and implement AI agents and automation scripts (primarily using Python) to transform network planning processes, including demand translation, topology generation, and L3-L1 mapping, leading the shift to intention-based planning.
- Build, test, and integrate modular, reusable "Agentic Skills" into the network planning pipeline to generate auto-validated Plans of Record (PORs), enhance efficiency, and minimize manual intervention, bypassing legacy UI limitations.
- Analyze network planning workflows to identify automation opportunities. Collaborate closely with cross-functional stakeholders to define automation requirements, ensure seamless integration of new tools and processes, and proactively resolve technical obstacles.
- Provide technical leadership and expertise in network automation, AI application in networking, data analysis, and software development best practices.
- Drive the adoption of innovative solutions and contribute to the technical strategy and roadmap for network planning automation.
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Requirements
Experience driving progress, solving problems, and mentoring more junior team members; deeper expertise and applied knowledge within relevant area., * Bachelor's degree in Computer Science, Engineering, a related field, or equivalent practical experience.
- 6 years of experience with network routing protocols, design and troubleshooting, with network equipment providers.
- Experience in one or more programming languages such as C++, Go, or Python., * Experience applying software development in network engineering, understanding network architectures (WAN, Campus), protocols, and capacity planning principles.
- Experience integrating automation tools with network systems and data sources via APIs, network models, and demand forecasting data.
- Proficiency in developing Python automation scripts and tools for solving complex network planning and design challenges like topology generation, capacity analysis, and Plan of Record (POR) creation.
- Familiarity with software development best practices, including version control, code reviews, testing, and documentation for network automation projects.
- Ability to use Python and libraries like Pandas to process, analyze, and visualize network datasets for data-driven decisions.