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Efficiency AI Ops Engineer Hybrid

Job in Raleigh, Wake County, North Carolina, 27601, USA
Listing for: Webex Events (formerly Socio)
Full Time position
Listed on 2026-07-11
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Job Description & How to Apply Below

AI Ops Engineer

This role is hybrid. Onsite three days per week in Raleigh (Research Triangle Park), North Carolina or San Jose, California.

Our team is part of the Cisco AI and Automation portfolio, responsible for the "Circuit" platform—the central AI engine that powers productivity and process automation for all of Cisco. We are a rapidly expanding, high-impact group dedicated to building the vehicle for AI-driven business transformation. We operate at the intersection of applied research and production, ensuring our technology is not only pioneering but also optimized for performance and cost-efficiency for our 80,000+ monthly users.

As an AI Ops Engineer, you will develop software consistent with Cisco's 'Design Thinking Principles,' with a core focus on simplification, UX, and secure coding practices. You will serve as a key driver in the evolution of our AI ecosystem, moving beyond standard development to explore, evaluate, and implement next-generation AI techniques. By partnering with product management and design teams, you will ensure our platform remains the most relevant and efficient tool for our wide range of users.

You will directly tackle high-impact technical challenges—such as optimizing LLM token usage, automating model routing, and fine-tuning LLM models—to ensure our platform scales effectively. You will harness advanced AI coding tools (such as Cursor, Copilot, or Claude Code) to align LLM performance (logical and speed) towards making AI generated code production ready. This is an opportunity to work on a high-visibility platform where your contributions to product innovation and development processes have a tangible, global impact on how Cisco runs its business.

Conduct applied research to evaluate and implement new AI techniques, such as automatic model routing and batch capacity management, to optimize cost and performance.

Where applicable propose and evaluate results of fine-tuning open source LLMs with sharply defined goal metrics. Compare these with similar out of box industry models.

Build, integrate, and maintain AI agents and features within the Circuit platform to drive process automation across the company.

Apply Agentic AI to modernize existing features in Circuit platform.

Continuously monitor the AI landscape to stack-rank and integrate new models from vendors while de-prioritizing underperforming technologies.

Serve as a "Team Captain" for specific features, driving consensus across multi-functional teams and mentoring peers to elevate the team's collective technical proficiency.

Lead the delivery of high-quality design features from initial concept through to production integration and performance measurement.

Bachelor's degree with 6+ years, Master's degree with 4+ years, or PhD with 1+ year of related experience in Computer Science, AI/ML, or a related technical field.

Proven experience conducting applied research to solve complex technical problems, including the evaluation and integration of new AI/ML technologies.

Solid conceptual and practical knowledge of AI/ML technologies, including LLMs, model fine-tuning, and their application in production environments. Curious, creative and track record of constant learning.

Demonstrated experience in software development with a focus on building, testing, and deploying scalable features in a production environment. Including vibe coding and deploying those artifacts. Hands-on experience using AI-assisted coding tools (e.g., Git Hub Copilot, Cursor, Claude Code) to build, validate, and deploy production-level software artifacts. Ability to read and judge the stability of the auto generated code, such that, it does not violate security standards.

Strong critical thinking skills with the ability to evaluate and document technical trade-offs regarding cost, quality, and performance.

Experience in AI Ops, MLOps, or building/fine-tuning custom LLMs to achieve well defined metrics.

Proven track record of leading technical projects and mentoring junior engineers.

Strong communication and collaboration skills; ability to influence multi-functional partners and work effectively within a team environment.

Experience with "Design…

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