Principal Machine Learning Engineer

The application window is expected to close on: 11/25/2026

About the Team The AI Software & Platform Team designs and builds enterprise AI platform software to enhance security resilience, threat defense, and operational automation across Cisco’s portfolio. The team consists of front-end, backend, and machine learning engineers developing core platform infrastructure, agentic frameworks, and AI-enabled product interfaces.

The AI Software & Platform Team designs and operates the core platform infrastructure connecting

Cisco’s enterprise product dashboards with intelligent, agentic AI capabilities. The team consists of front-end, backend, machine learning engineers and applied AI researchers developing core platform infrastructure, agentic frameworks, and AI-enabled product interfaces.

Your Impact As a Principal Software Engineer, you will serve as a lead technical architect and technical authority for the AI Platform Engineering team. In this role, you will define the architectural vision, lead system design, and direct technical execution for the Agentic Ops Solution (AI Canvas) and associated AI platform capabilities. You will drive technical standards, evaluate emerging technologies, and collaborate with product management and engineering teams to deliver scalable AI systems.

Key Responsibilities An AI-first mindset paired with the ability to exercise sound technical judgment and decompose vague, complex problems into well-scoped, actionable deliverables.

Experience building shared infrastructure, abstractions, and "paved roads" that enhance productivity across engineering teams.

Proficiency in spec-driven and schema-driven development, including the use of code generation, strongly typed API contracts, and implementation traceability.

Understanding of the unique architecture and operational constraints associated with both SaaS and on-premise deployment models.

Ability to mentor immediate team members while effectively driving technical decision-making across cross-functional and cross-organizational boundaries.

Experience building LLM / agentic systems: orchestrators, ReAct-style and deep agents, tool calling, MCP servers, streaming and asynchronous task results, and disambiguation in conversation.

Experience running services on Kubernetes, including deployment configuration, secret management, and health checks, and working closely with SRE.Strong debugging skills across service boundaries using logs, traces, and metrics.

Clear technical writing and the ability to lead design reviews with engineers, QA, product, and security.

Minimum qualifications

Education & Experience:

Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, or related technical field with 15+ years of software engineering experience; OR Master’s degree with 12+ years; OR PhD with 8+ years

Platform & Cloud Systems

Experience:

Minimum of 8 years of experience designing and deploying distributed cloud software platforms, microservices, or enterprise-scale automation systems.

Technical Leadership Track Record:
Minimum of 4 years serving in a technical leadership capacity (e.g., Principal Engineer, Lead Architect, or Technical Lead) driving architectural decisions across multi-disciplinary engineering teams.

AI Software Development Lifecycle (AI-SDLC):
Experience leveraging code gen tools for software development leading to significant productivity improvements.

AI Applications:
Experience building and deploying production applications utilizing Generative AI, LLM orchestration frameworks, or AI assistants/copilots.

Core Engineering Proficiency:
Experience developing backend or full-stack software using modern languages (e.g., Python, Go, or Type Script/Node.js) and cloud-native technologies (e.g.,…