Distinguished Machine Learning Engineer, AISWP; Hybrid

The application window is expected to close on: 10/04/2026

Cisco’s AI Software & Platform team (AISWP) is the heartbeat of Cisco’s AI transformation. We aren't just integrating AI; we are building the infrastructure that defines how the internet is managed. As a Distinguished Machine Learning Engineer, you will have a seat at the table where the future of autonomous, agentic networking is designed. Working directly alongside senior executive leadership, you will lead the architecture for Cisco Cloud Control and Canvas—the cornerstone platforms that are shifting Cisco from a collection of products to a unified, AI-driven Agentic Ops powerhouse.

This is a rare opportunity to move the needle on a global scale, solving high-stakes challenges that directly impact our customers' ability to run their most critical infrastructure.

You will be the bridge between cutting-edge AI research and massive-scale engineering. You will collaborate with our most senior AI researchers, distributed systems architects, and product visionaries to turn abstract technical possibilities into production reality. You will serve as the primary technical advocate, driving alignment across Cisco’s broad engineering organization to ensure our AI services are secure, scalable, and genuinely transformative.

As a Distinguished Machine Learning Engineer, you will own the technical trajectory of our platform. Your influence will be felt in every layer of the stack, from model context strategies to the security guardrails that keep customer production environments safe.

• Define and implement multi-year technical strategies for agentic systems, ensuring unified architectural alignment across Cisco’s broad product portfolio and global engineering organizations.
• Serve as the primary internal and external technical authority, negotiating critical architectural decisions with senior executives and driving the adoption of industry standards, such as the Model Context Protocol (MCP).
• Architect complex systems that use hybrid and graph-based retrieval, creating unique, scalable solutions for cross-product telemetry, root cause analysis, and automated remediation.
• Establish the company-wide standards for AI safety, observability, and compliance, ensuring that all agent-based autonomous actions remain measurable, auditable, and resilient to production risks.
• Cultivate a high-performance engineering culture by mentoring Principal and Senior-level leaders, fostering innovation, and representing Cisco’s technical excellence at industry forums, standards bodies, and global conferences.

• Bachelor’s degree in computer science or a related field with 17+ years of total software engineering experience;
  Master's with 14+ years; or PhD with 10+ years.
• 5+ years of experience operating at a "Principal" level or above, with documented proof of influencing technical strategy across at least 3 distinct product organizations.
• 2+ years of experience in the design, development, and production-level deployment of LLM-based systems serving at least 10,000+ daily active users or processing 500+ requests per second.
• Successfully architected and shipped at least 1 production-grade multi-agent system using frameworks such as Lang Graph, Temporal, or an equivalent complex state-machine stack.
• 10+ years of deep experience writing production-grade code in Go, Python, or Rust, specifically within hyperscale environments (e.g., managing architectures supporting 100+ microservices or petabyte-scale data pipelines).
• Experience designing and implementing at least 3 critical safety or observability features in a production environment (e.g., indirect prompt injection defense, human-in-the-loop gates, or automated rollbacks).