AI LLMOps Engineering Technical Leader

Cisco

Confirmed live today High trust
Hybrid

Quick summary

Work type
Hybrid
Location
San Jose, CA
Salary
$216,300–$280,800 / yr
Employment
Full-time
Posted
68 days ago
Freshness
Confirmed live today
Closes
Nov 27, 2026

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $206k
This role $249k
$137k $296k
below market most similar roles pay here above market

This role pays more than 83% of similar roles. Most pay $176,100–$236,812 — the blue band above. At the midpoint, this role pays about $249k versus about $206k 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 307 open roles on FindRole.

Listed pay typically runs $167,700–$245,000 across 224 roles with salary data.

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At a glance

TL;DR · AI LLMOps Engineering Technical Leader

The AI LLMOps Engineering Technical Leader joins the Customer Reliability Engineering group within the Customer Experience Engineering organization. This role focuses on operationalizing complex autonomous agent architectures into secure, scalable, and high-performing production environments. You will define MLOps practices, establish foundational ML pipelines, and design model serving architectures to transition Agentic AI concepts into customer-facing products. Daily responsibilities include implementing telemetry monitoring for token usage and compute costs, managing containerized models on GPU clusters, and resolving inference issues. Required skills include Python, Java/J2EE, and experience with frameworks like FastAPI, Flask, or Spring Boot. You must possess expertise in LLMs such as OpenAI, Anthropic, or Llama, alongside tools like LangChain, Docker, Kubernetes, and MLOps platforms like MLflow or Weights & Biases.

What you'll do

  • Operationalize complex autonomous agent architectures into secure, scalable, and high-performing production environments.
  • Establish robust MLOps practices, foundational ML pipelines, and model serving architectures for Agentic AI.
  • Design and implement telemetry monitoring tools to track token usage, compute costs, and model performance.
  • Manage containerized models on GPU clusters and resolve complex model inference issues.
  • Guide architectural choices regarding GPU compute scaling, model latency, and AI routing.
  • Identify and mitigate risks regarding prompt injection and AI data leakage through threat modeling.
  • Lead postmortems and mentor junior team members on technical designs and architectural choices.

What we're looking for

  • Bachelor's degree and 8+ years of related experience, or Master's degree and 6+ years of related experience.
  • Experience in Software Engineering and DevOps job families, specifically building scalable infrastructure.
  • Experience operationalizing Large Language Models (e.g., OpenAI, Anthropic, Llama) and utilizing frameworks like LangChain or LangSmith.
  • Experience in Python and/or Java/J2EE.
  • Experience developing robust APIs using frameworks such as FastAPI, Flask, or Spring Boot.
  • Experience with CI/CD for machine learning, MLOps frameworks (e.g., MLflow, ClearML), and containerization using Docker and Kubernetes.
  • Expertise in Agentic AI, including designing and deploying autonomous systems and multi-agent workflows (preferred).
  • Ability to articulate architectural choices regarding GPU scaling, latency, and AI routing, including knowledge of API gateways (preferred).

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