This role pays more than
82%
of similar roles. Most pay
$175,500–$245,625
— the shaded band above.
At the midpoint, this role pays about
$249k
versus about
$211k
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.
AI LLMOps Engineering Technical Leader
The AI LLMOps Engineering Technical Leader joins the Customer Reliability Engineering group to ensure high-performing production systems for the customer experience platform. This role focuses on operationalizing complex autonomous agent architectures into secure, scalable environments while establishing robust MLOps practices and model serving infrastructures. You will build telemetry monitoring tools to track token usage, manage compute costs, and monitor reasoning paths. The work involves managing containerized models on GPU clusters and resolving inference issues within hybrid cloud environments. Key technologies include Python, Java/J2EE, and frameworks like FastAPI, Flask, or Spring Boot. Required skills involve experience with LLMs such as OpenAI, Anthropic, and Llama, alongside tools like LangChain, LangSmith, Docker, Kubernetes, and MLOps platforms like MLflow or Weights & Biases. You will also navigate architectural trade-offs regarding latency, accuracy, and cost while mitigating risks like prompt injection.
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 products.
Design and implement telemetry monitoring tools to track token usage, compute costs, and reasoning paths.
Resolve infrastructure challenges involving containerized models on GPU clusters and address model inference issues.
Guide architectural choices regarding GPU scaling, model latency, and AI routing based on market knowledge.
Mitigate security risks such as prompt injection and AI data leakage through threat modeling.
Lead postmortems, mentor junior team members, and facilitate technical knowledge-sharing sessions.
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 with a focus on building scalable infrastructure.
Experience operationalizing Large Language Models using frameworks like LangChain or LangSmith.
Proficiency 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 tools (ClearML, MLflow, Weights & Biases), and containerization via 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, model latency, and threat modeling for prompt injection or data leakage (preferred).
Remote (Silver Spring, MD)21 days ago
$204,000–$276,000
Artificial Intelligence
Machine Learning
Python
R
Java
TensorFlow
PyTorch
AWS SageMaker
Retrieval-Augmented Generation (RAG)
Agentic AI
AWS Bedrock
Azure AI Foundry
Google Vertex AI
Salesforce
Agentforce
MLOps
Zero Trust
Data Engineering
Cloud Computing