Description
Our organization is at the forefront of Cisco’s strategic evolution into the Full-stack AI market. We are a specialized, high-impact team dedicated to building and scaling the next generation of AI infrastructure solutions.
As a Senior Technical Marketing Engineer and Technical Leader, you will serve as the primary technical authority for new AI Infrastructure initiative, 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.
Responsibilities:
- 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.
Benefits:
- Medical, dental and vision insurance
- 401(k) plan with a Cisco matching contribution
- Paid parental leave
- Short and long-term disability coverage
- Basic life insurance
- Paid time away (vacation, holidays, sick time)
- Optional 10 paid days per full calendar year to volunteer