The application window is expected to close on: 11/29/2026
This is a Hybrid job located in San Jose or New York, 2 days in office will be required.
Your Impact
As a Senior Technical Marketing Engineer and Technical Leader, you will serve as the primary technical authority for new AI Infrastructure initative, bridging the gap between sophisticated engineering development and customer-facing deployment. You will own the technical narrative, validating the end-to-end lifecycle of our solutions to ensure they meet the rigorous demands of real-world enterprise environments. By translating field feedback and adoption blockers into actionable technical requirements, you will directly influence our product roadmap and ensure our technology is ready for global scale. Your work will define how customers perceive, adopt, and derive value from Cisco's most critical new product innovations.
• Collaborate with engineering and product management to identify product gaps, resolve adoption blockers, and define technical readiness criteria.
• Produce technical assets such as white papers, deployment guides, demonstration videos, and workshops to enable internal field teams and external partners.
• Represent the product and technical strategy in customer workshops, executive briefings, and strategic industry forums.
Minimum Qualifications
• Bachelor's degree in Engineering + 8 years of professional experience, or a Master's degree + 6 years of professional experience.
• 4 years of experience in technical marketing, solutions architecture, systems engineering, or platform/site reliability engineering.
• Hands-on Experience deploying and managing Kubernetes clusters in production or production-like environments, including container orchestration, networking, and storage integrations.
• Working knowledge of Linux and infrastructure fundamentals, including networking, storage, access controls, and observability.
• Experience developing infrastructure automation using scripting languages (e.g., Python, Go) or infrastructure-as-code tools (e.g., Terraform, Ansible).
• Experience creating and delivering technical presentations or documentation, such as white papers, deployment guides, or architectural design reviews, for technical audiences.
• Ability to learn unfamiliar technologies and apply them to practical lab or customer scenarios.
Preferred Qualifications
• Experience with AI/ML infrastructure, specifically managing GPU clusters, model training pipelines, or AI-workload placement within Kubernetes.
• Familiarity with GPU monitoring, resource sharing, or performance evaluation.
• Experience with public or private cloud platforms, including multi-tenancy, identity and access management, and observability frameworks.
• Operational experience with SRE methodologies, including incident response, capacity planning, and performance benchmarking.
• Experience working in agile, rapid-growth environments where product requirements and technical priorities evolve continuously.
