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Extreme Networks

Senior AI/ML Engineer – Generative AI & Autonomous Agents

Hybrid Engineering
Added
1 day ago
Location
Type
Full time
Salary
Not Specified

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Related skills

python prompt engineering rag langchain generative ai

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 Engineerwith  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.

Key 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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