Über diese Senior Director of Engineering - Next-generation Network OS for Switching and routing Infrastructure-10393 Stelle bei Extremenetworks
Role Overview
We are seeking a Senior Director of Engineering to lead the strategy, development, and delivery of next-generation Network OS for Switching and routing Infrastructure. This leader will drive innovation through AI-assisted development practices, build high-performing teams, and ensure consistent delivery of high-quality, metrics-driven outcomes at scale.
The ideal candidate brings deep domain expertise in networking infrastructure combined with modern software development leadership and a strong track record of adopting AI/ML tools to accelerate engineering productivity and product quality.
Key Responsibilities
Leadership Profile & Strategy
· Define and execute engineering strategy for Next-gen Network OS
· Lead and mentor globally distributed engineering teams, fostering a culture of innovation, accountability, and operational excellence
· Partner with Product, Architecture, and Customer Success teams to align roadmaps with business goals and customer needs
· Drive organisational transformation toward AI-assisted engineering practices
· Strategic thinker with strong execution focus
· Data-driven decision-maker
· Passion for innovation and continuous improvement
· Collaborative and influential across organisational boundaries
· Strong advocate for engineering excellence and customer value
Engineering Excellence
· Establish and enforce quality, reliability, and performance standards
· Champion modern, data-driven engineering practices, leveraging delivery performance, developer experience, and AI-assisted productivity metrics to drive continuous improvement and high-quality outcomes
· Foster a fail-fast, learn-fast culture by encouraging rapid experimentation, iterative development, and quick feedback loops to accelerate innovation while minimizing risk
· Promote blameless postmortems and continuous learning to improve systems, processes, and team effectiveness
AI-Driven Development
· Lead adoption of AI-assisted development tools (e.g., code generation, automated testing, observability, and incident response automation)
· Integrate AI/ML into engineering workflows to:
· Accelerate development velocity
· Improve code quality and defect detection
· Enhance operational insights and automation
· Promote best practices for responsible and secure use of AI in engineering
Delivery & Execution
· Drive predictable and high-quality software releases across multiple product lines
· Ensure programs are delivered on time, within scope, and aligned with strategic objectives
· Establish robust CI/CD pipelines and DevSecOps practices
· Continuously improve engineering processes based on data and feedback
Stakeholder Management
· Communicate effectively with executive leadership and cross-functional stakeholders
· Provide regular updates on roadmap execution, risks, and performance metrics
· Represent engineering in customer and partner engagements.
Qualifications Required
· 20+ years of engineering experience, with 5+ years in senior leadership roles
· 7+ years leading large, global engineering teams, including India-based and US-based organizations.
· Proven expertise in networking technologies, including Data centre, Enterprise solutions.
· Demonstrated success leading large-scale, distributed engineering teams
· Strong track record of delivering high-quality, scalable products using metric-driven approaches
· Hands-on experience driving adoption of AI-assisted software development tools and practices
· Deep understanding of cloud-native architectures, microservices, and distributed systems
· Experience with DevOps/DevSecOps frameworks and CI/CD pipelines
Preferred Quaifications
· Familiarity with observability, telemetry, and data-driven operations
· Knowledge of security principles related to networking and infrastructure
· Bachelor’s or Master’s degree in Computer Science, Engineering, or related field
Key Success Metrics
· Improvement in engineering velocity and predictability
· Reduction in production defects and MTTR
· Adoption rate and impact of AI-assisted development tools
· Platform reliability, scalability, and customer satisfaction (SLAs, NPS)
· Employee engagement and retention within engineering teams