The application window is expected to close on: 07/17/2026
Job posting may be removed earlier if the position is filled or if a sufficient number of applications are received.

This position is based in Unitad States and operates under a hybrid work model prefered location San Jose California , North Carolina and Seattle.

Your Impact

You will define the long-term architecture for Cisco's enterprise AI platform, encompassing agentic systems, multi-agent orchestration, LLM integration, search and AI convergence, retrieval and memory frameworks, evaluation and reliability systems, human-in-the-loop controls, and scalable data pipelines. Your work will ensure the platform remains modular, secure, resilient, interoperable, and future-ready.

You will lead the design and resolution of the organization's most complex technical challenges, including multi-agent system reliability, orchestration frameworks, long-term context retention, model routing, retrieval patterns, trust mechanisms, and enterprise-scale AI performance. You will set architectural principles and reference patterns that reduce fragmentation and enable consistent execution across the eight-pillar operating model.
You will create and drive a clear path that converts advanced technical invention into production-grade platform capabilities. Partnering closely with Platform Engineering, you will ensure new ideas are designed for production from the outset and hardened into operationally ready services. In collaboration with Product Management, you will align technical innovation with CIRCUIT's long-term roadmap and value proposition.
You will act as the primary architectural bridge across Platform Engineering, Solutions Engineering, Process Engineering, Product, and other Cisco business units, driving alignment on standards, frameworks, and reference architectures. You will work across corporate functions to ensure internal AI efforts build on CIRCUIT in a way that is secure, interoperable, and extensible.
You will lead rapid exploration of emerging areas such as agent collaboration, autonomous planning, practive workflows, tool use, long-term memory, and new interaction models, evaluating technical feasibility, scalability, and enterprise readiness. You will stay closely connected to advances in AI research, open-source ecosystems, model providers, cloud platforms, and enterprise AI frameworks, guiding adoption where it creates durable advantage for Cisco.
You will represent Cisco as a recognized technical authority in enterprise AI, engaging with research communities, partners, customers, and industry ecosystems. You will translate complex technical strategy into clear direction for executives, senior engineering leaders, and strategic stakeholders, and support high-level customer and partner conversations by articulating Cisco's AI architecture approach and lessons learned from operating CIRCUIT at scale.
You will elevate the technical maturity of the organization through mentorship, architectural reviews, standards setting, and guidance. You will coach senior engineers and technical leaders, build a strong bench of architectural talent, develop a culture of high-velocity experimentation and rigorous engineering quality, and contribute to Cisco's technical reputation through patents, white papers, architectural standards, and thought leadership.

Minimum Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
• 17+ years of experience in software engineering, technical architecture, distributed systems, AI/ML, or platform engineering; advanced degree may substitute for some experience.
• Demonstrated experience as a principal engineer, architect, or senior technical leader in large-scale enterprise environments
• Proven ability to define technical strategy and drive architectural direction across multiple organizations and business domains
• Strong background of leading complex, multi-functional technical initiatives from concept through production
• Experience with AI/ML systems, distributed systems, cloud-native infrastructure, or large-scale data platforms
• Demonstrated history of architectural influence through standards, patents, publications, technical papers, or comparable contributions

Preferred Qualifications

• Deep expertise in generative AI, LLM integration, multi-agent systems, RAG, evaluation frameworks, and enterprise AI architecture.
• Experience taking research concepts or early prototypes through productization into secure, scalable, production-ready offerings
• Strong familiarity with model orchestration, memory systems, tool invocation, agent reliability, and enterprise trust controls
• Experience in multi-cloud and hybrid environments, including GCP, AWS, Azure, and on-prem infrastructure
• Strong network within AI research, open-source, or partner ecosystems.
• Experience mentoring engineering teams in high-velocity, experimental environment
• Prior customer-facing or partner-facing experience providing technical strategy, architecture guidance, or executive-level AI advisory support
• Experience with enterprise search, data integration, developer platforms, or large-scale internal productivity systems