Senior Engineering Manager- AI/ML & networking

Key Responsibilities

• Lead a team of engineers working on AI-driven solutions in the networking and network security domain
• Act as a hands-on technical leader, guiding design, architecture, and implementation
• Work closely with customers, solution architects, and delivery teams to understand requirements and propose solutions
• Collaborate with client product managers, architects, and engineering stakeholders to align on technical direction, scope, and roadmap
• Drive execution of AI-based automation, analytics, and optimization use cases in networking projects
• Ensure timely delivery of high-quality software aligned with client expectations
• Stay abreast of industry trends in AI and networking to identify innovation opportunities
• Foster a collaborative and performance-driven culture within the team
• Lead internal product accelerators and contribute to reusable solution assets and frameworks
• Drive engineering best practices including Agile/Scrum methodologies, CI/CD, code quality, design reviews, and architecture decision records
• Oversee hiring and onboarding of engineers; collaborate with recruitment to build high-caliber teams
• Identify and manage risks proactively, including technical, resourcing, and delivery-related risks
• Coach, mentor, and grow engineering leads and senior developers; foster a culture of learning, collaboration, and ownership

Basic Qualifications

• 8+ years of experience in engineering roles, with at least 2 years in a team leadership or engineering management capacity (or 12+ years with 4+ years in leadership roles)
• Proven experience in projects at the intersection of AI/ML and networking technologies
• Deep understanding of network communication protocols (e.g., TCP/IP, SNMP, BGP, OSPF)
• Practical knowledge of AI/ML tools and frameworks (e.g., Python, TensorFlow, PyTorch, Scikit-learn)
• Strong problem-solving and analytical skills with a hands-on mindset
• Proven experience managing multiple product engineering teams in a client-facing services environment
• Excellent communication and stakeholder engagement skills
• Knowledge of cloud-native platforms (AWS, Azure, GCP), containerization, and microservices

Preferred Qualifications

• Experience working with OEMs, MSPs, or service providers in the networking domain
• Understanding of SDN, NFV, or cloud networking architectures (AWS, GCP, Azure)
• Exposure to AI/ML Ops tools (e.g., MLflow, Kubeflow, SageMaker)
• Ability to manage cross-functional teams and lead delivery across multiple projects
• Excellent communication and stakeholder engagement skills (reiterated for emphasis due to client-facing nature)