LLM Engineer

• lead the product marketing strategy for Cisco’s AI infrastructure portfolio
• connect technical capabilities to the business outcomes customers require for AI workloads and AI-native applications
• define the narrative, positioning, messaging, launch strategy, and sales enablement required to power secure, connected, AI-ready organizations
• partner with Product Management, Engineering, Sales, Corporate Marketing, Analyst Relations, and Communications
• translate sophisticated infrastructure innovation into market value
• drive cross-functional alignment
• equip the business to win with enterprise buyers and executives

Director of Product Marketing Strategy – AI Infrastructure

• Define and evolve the long-term AI/ML research strategy and technical roadmap for Trase OS in alignment with product and platform direction.
• Lead large-scale experimentation and prototyping efforts requiring significant compute infrastructure, translating frontier AI research into scalable, production-grade systems with measurable impact.
• Drive original research and technical breakthroughs in agentic systems, autonomous execution, multi-agent orchestration, post-training and fine-tuning systems, SLM/LLM-based architectures, and applied AI infrastructure.
• Design how models operate within long-lived execution environments, including agent workflows, tool use, planning, memory systems, reasoning, and human-in-the-loop controls.
• Establish evaluation methodologies and reliability frameworks for autonomous systems, including benchmarking, regression testing, safety, controllability, and production behavior analysis.
• Drive architecture decisions across orchestration, model serving, routing, inference, and infrastructure governance, including latency, reliability, and cost optimization.
• Partner closely with engineering and product teams to operationalize research outcomes into deployable systems and enterprise workflows.
• Build AI systems that operate reliably in regulated and constrained environments, including secure cloud, on-premise, and air-gapped deployments.
• Contribute to the broader AI research community through technical papers, publications, conference participation, architecture proposals, and thought leadership.
• Serve as a senior technical authority and mentor across the organization, influencing technical direction, research rigor, experimentation practices, and best practices across research, engineering, and product teams.

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