Hybrid AI Ops Engineer - AI Platform & Automation

Cisco Systems, Inc.; San Jose, Northern (CA, KY); Hybrid; USD 200,000 - 255,000; Full time

Job summary

Cisco Systems, Inc. in the United States is seeking an AI Ops Engineer to advance the Circuit platform, focusing on simplifying UX and secure coding.

You will explore, evaluate, and implement next-generation AI techniques, optimizing LLM usage and model routing to scale the service for Cisco's 80,000+ monthly users. You will collaborate with product, design, and security teams to ensure production‑level software artifacts, evidence-based decisions, and cost-efficient deployments across Cisco's

Qualifications

• Advanced degree in CS/AI/ML with relevant experience.
• Proven applied research experience in AI/ML and deployment.
• Experience with LLMs, fine-tuning, and production systems.
• Hands-on with AI-assisted coding tools to ship production artefacts.

Responsibilities

• Research and implement new AI techniques to optimize cost and performance.
• Evaluate open-source LLMs and compare with industry models.
• Develop AI agents and features within Circuit platform.
• Modernize features using Agentic AI in Circuit.
• Monitor AI landscape and integrate new models while de-prioritizing others.
• Serve as Team Captain driving consensus and mentoring peers.
• Lead design feature delivery from concept to production and measurement.

Skills

AI/ML knowledge

LLMs fine-tuning

AI coding tools

Team leadership

Design Thinking

Production-grade code

Performance optimization

Applied AI research

Education

Bachelor's degree

Master's degree

PhD

Tools

GitHub Copilot

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Claude Code

Job description

Cisco Systems, Inc. in the United States is seeking an AI Ops Engineer to advance the Circuit platform, focusing on simplifying UX and secure coding.

You will explore, evaluate, and implement next-generation AI techniques, optimizing LLM usage and model routing to scale the service for Cisco's 80,000+ monthly users. You will collaborate with product, design, and security teams to ensure production‑level software artifacts, evidence-based decisions, and cost-efficient deployments across Cisco's