Efficiency AI Ops Engineer

Cisco

Confirmed live yesterday High trust
Hybrid

Quick summary

Work type
Hybrid
Location
Raleigh, NCSan Jose, CA
Salary
$203,000–$258,600 / yr
Posted
7 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $178k
This role $231k
$114k most similar roles pay here $274k

This role pays more than 82% of similar roles. Most pay $142,400–$214,000 — the shaded band above. At the midpoint, this role pays about $231k versus about $178k for comparable roles.

Based on 240 similar postings.

Employer

About Cisco

Cisco Systems is the world''s leading networking technology company, designing and manufacturing networking hardware, telecommunications equipment, and cybersecurity solutions for businesses and governments. Industry: Networking Technology & Cybersecurity

Cisco currently has 196 open roles on FindRole.

Listed pay typically runs $167,700–$245,200 across 196 roles with salary data.

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View all roles at Cisco

At a glance

TL;DR · Efficiency AI Ops Engineer

Efficiency AI Ops Engineer Hybrid joins the Cisco AI and Automation team to support the Circuit platform, which serves as the central engine for internal productivity and process automation. This role involves conducting applied research to evaluate new AI techniques, such as automatic model routing, batch capacity management, and fine-tuning open-source LLMs against specific performance metrics. The engineer will build, integrate, and maintain AI agents while utilizing advanced tools like Cursor, Copilot, and Claude Code to ensure generated code is production-ready and secure. Key responsibilities include managing token optimization, monitoring the AI landscape to stack-rank vendor models, and leading feature delivery from concept to integration. The role requires expertise in LLMs, MLOps, and Agentic AI to solve complex technical challenges regarding cost, quality, and performance within a high-visibility internal platform.

What you'll do

  • Conduct applied research to evaluate and implement new AI techniques like automatic model routing and batch capacity management.
  • Propose and evaluate the results of fine-tuning open-source LLMs against specific goal metrics and industry models.
  • Build, integrate, and maintain AI agents and features within the Circuit platform to drive process automation.
  • Apply Agentic AI to modernize existing features and improve functionality within the core platform.
  • Monitor the AI landscape to rank and integrate new vendor models while de-prioritizing underperforming technologies.
  • Serve as a Team Captain to lead feature development, mentor peers, and drive consensus across multi-functional teams.
  • Utilize AI-assisted coding tools to develop, validate, and deploy production-ready software artifacts that meet security standards.
  • Manage technical trade-offs regarding cost, quality, and performance while delivering high-quality design features from concept to production.

What we're looking for

  • Bachelor's degree with 6+ years, Master's degree with 4+ years, or PhD with 1+ year of experience in Computer Science, AI/ML, or a related field.
  • Proven experience conducting applied research to solve complex technical problems and integrating new AI/ML technologies.
  • Solid conceptual and practical knowledge of LLMs, model fine-tuning, and their application in production environments.
  • Demonstrated experience in software development for building, testing, and deploying scalable features in a production environment.
  • Hands-on experience using AI-assisted coding tools like GitHub Copilot, Cursor, or Claude Code to build and deploy production-level artifacts.
  • Ability to evaluate the stability of auto-generated code to ensure it meets security standards.
  • Strong critical thinking skills to evaluate and document technical trade-offs regarding cost, quality, and performance.
  • Experience in AI Ops, MLOps, or building agentic applications with a focus on evaluation and business acceptance.

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