The application window is expected to close on: 09/29/2026
Job posting may be removed earlier if the position is filled or if a sufficient number of applications are received.
Meet the TeamThe Cisco IQ and
Validation team is building the next generation of intelligent, AI-driven network validation and automation capabilities. We combine cloud-native software engineering, Agentic AI, LLMs, MCP, A2A, and network automation to enable customers to validate and operate complex environments more intelligently. The team brings together architects, senior engineers, software engineers, AI specialists, and domain experts working across a global organization. We are building foundational capabilities that will enable AI agents to reason, interact with enterprise tools, and safely execute validation workflows at scale.
Your ImpactDefine and drive the architecture for
AI decision systems, Agentic AI platforms, and enterprise-scale validation and automation capabilities within Cisco IQ and Validation. Establish technical direction for agent architectures, MCP and A2A integrations, agent routing, tool orchestration, workflow execution, approval-gated actions, and distributed event-driven systems. Guide architecture across backend services, APIs, databases, Kubernetes, cloud infrastructure, observability, and production operations to ensure solutions are scalable, secure, reliable, and maintainable. Drive technical alignment across Engineering, Product, UX, Security, Infrastructure, QA, and partner teams and provide technical leadership for complex, ambiguous, cross-functional initiatives. Mentor senior engineers and technical leads while influencing platform strategy, engineering standards, and the long-term evolution of Validation.
Minimum Qualifications- Bachelor's degree in STEM, 8+ years of software engineering experience designing and building complex backend, distributed, automation, or platform systems.
- Experience with Python Go, Rust, TypeScript, React, Node.js, .NET, PostgreSQL, Redis, Kafka, or similar technologies.
- Experience designing distributed systems using APIs, databases, event-driven architectures, workflow systems, or cloud-native technologies.
- Experience developing or architecting Generative AI, LLM, Agentic AI, MCP, A2A, or AI-enabled automation systems.
- Experience with Kubernetes, Docker, CI/CD, cloud platforms, and production software operations.
- Experience designing advanced multi-agent architectures, including planner/executor patterns, agent handoffs, state management, checkpointing, retries, cancellation, or durable workflows.
Preferred Qualifications- Experience designing AI quality, evaluation, observability, and governance frameworks.
- Experience with network automation, device connectivity, validation platforms, infrastructure automation, or enterprise network systems.
- Experience leading architecture across multiple engineering teams and influencing technical strategy, standards, and platform roadmaps.
- Experience architecting MCP and A2A systems, including capability discovery, tool schemas, authentication, context propagation, streaming, approval gates, auditability, and failure handling.