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Senior AI/ML Engineer Generative AI & Autonomous Agents (10034, 10035)
Senior AI/ML Engineer Generative AI & Autonomous Agents (10034, 10035)Extreme Networks • Seattle, Washington, United States
Senior AI / ML Engineer Generative AI & Autonomous Agents (10034, 10035)

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

Extreme Networks • Seattle, Washington, United States
[job_card.30_days_ago]
[job_preview.job_type]
  • [job_card.full_time]
[job_card.job_description]

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 .

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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