Senior AI/ML Engineer – Generative AI & Autonomous Agents (10034, 10035)

Overview

At Extreme Networks, we create effortless networking experiences that empower people and organizations to advance. As part of our growing AI Competence Center, we are seeking a

Senior AI/ML Engineer

with expertise in

Generative AI ,

multi-agent systems , and

LLM-based application development . In this role, you will help build the next generation of

AI-native systems

that combine traditional machine learning, generative models, and autonomous agents. Your work will power intelligent, real-time decisions for

network design ,

optimization ,

security , and

support . Responsibilities

Design and implement the

business logic and modeling

that governs agent behavior, including decision-making workflows, tool usage, and interaction policies. Develop and refine

LLM-driven agents

using prompt engineering, retrieval-augmented generation (RAG), fine-tuning, or function calling. Understand and model the

domain knowledge

behind each agent: engage with network engineers, learn the operational context, and encode this understanding into effective agent behavior. Apply

traditional ML modeling techniques

(classification, regression, clustering, anomaly detection) to enrich agent capabilities. Contribute to the

data engineering pipeline

that feeds agents, including data extraction, transformation, and semantic chunking. Build modular, reusable AI components and integrate them with

backend APIs ,

vector stores , and

network telemetry pipelines . Collaborate with other AI engineers to create

multi-agent workflows , including planning, refinement, execution, and escalation steps. Translate GenAI prototypes into

production-grade , scalable, and testable services in collaboration with platform and engineering teams. Work with frontend developers to design agent experiences and contribute to

UX interactions

with human-in-the-loop feedback. Stay up to date on trends in LLM architectures, agent frameworks, evaluation strategies, and GenAI standards. Qualifications

Master’s or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field. 5 years of experience in ML/AI engineering, including 2 years working with

transformer models or LLM systems . Strong knowledge of

ML fundamentals , with hands-on experience building and deploying traditional ML models. Solid programming skills in

Python , with experience integrating AI modules into

cloud-native microservices . Experience with

LLM frameworks

(e.g., LangChain, AutoGen, Semantic Kernel, Haystack), and

vector databases

(e.g., FAISS, Weaviate, Pinecone). Familiarity with

prompt engineering

techniques for system design, memory management, instruction tuning, and tool-use chaining. Strong understanding of

RAG architectures , including semantic chunking, metadata design, and hybrid retrieval. Hands-on experience with

data preprocessing, ETL workflows , and embedding generation. Proven ability to work with

cloud platforms

like

AWS

or

Azure

for model deployment, data storage, and orchestration. Excellent collaboration and communication skills, including cross-functional work with product managers, network engineers, and backend teams. Nice to Have

Experience with

LLMOps tools ,

open-source agent frameworks , or orchestration libraries. Familiarity with

Docker ,

Docker Compose , and container-based development environments. Background in enterprise networking, SD-WAN, or network observability tools. Contributions to open-source AI or GenAI libraries.

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