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

Toronto, Ontario, Canada

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Networking, TechnologyIndustries

Requirements

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

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

Skills

Key technologies and capabilities for this role

Generative AIMulti-Agent SystemsLLMPrompt EngineeringRAGFine-tuningFunction CallingClassificationRegressionClusteringAnomaly DetectionData EngineeringVector StoresBackend APIsNetwork Telemetry

Questions & Answers

Common questions about this position

What qualifications and experience are required for this Senior AI/ML Engineer role?

A Master’s or PhD in Computer Science, AI, ML, or related field is required, along with 5+ years of ML/AI engineering experience including 2+ years with transformer models or LLMs, strong ML fundamentals, and Python programming skills.

What specific technical skills and tools are needed for this position?

Key skills include experience with LLM frameworks like LangChain, AutoGen, Semantic Kernel, Haystack; vector databases such as FAISS, Weaviate, Pinecone; prompt engineering, RAG architectures, and data preprocessing/ETL workflows.

What is the compensation or salary for this role?

This information is not specified in the job description.

Is this a remote position, or what is the location policy?

This information is not specified in the job description.

What kind of collaboration and team environment can I expect in this role?

You will collaborate with other AI engineers on multi-agent workflows, work with network engineers to model domain knowledge, partner with platform and engineering teams for production services, and team up with frontend developers for UX design.

Extreme Networks

Provides advanced networking solutions and services

About Extreme Networks

Extreme Networks specializes in advanced networking solutions that optimize and secure network operations for a variety of clients, including educational institutions, retail businesses, government agencies, and healthcare facilities. Their products include network infrastructure such as switching and routing solutions, wireless connectivity, and data center fabrics, along with cloud-based services and advanced security measures. Extreme Networks differentiates itself by offering both hardware and software solutions, as well as professional and managed services that ensure efficient network operations. Their goal is to provide comprehensive support and training to help clients maximize their networking capabilities.

Morrisville, North CarolinaHeadquarters

1996Year Founded

$16.8MTotal Funding

IPOCompany Stage

Government & Public Sector, Enterprise Software, Cybersecurity, EducationIndustries

1,001-5,000Employees

Benefits

Competitive pay

Comprehensive healthcare

HSA

Life & disability insurance

Retirement plans

Employee stock purchase program

Tuition reimbursement

PTO

Wellness programs

Risks

Securities fraud lawsuit may damage Extreme Networks' reputation and investor confidence.

Complexity of AI integration could hinder adoption of Extreme Platform ONE.

Stiff competition in cybersecurity market may affect ZTNA solution's market share.

Differentiation

Extreme Networks offers AI-powered platformization with Extreme Platform ONE.

The company provides comprehensive networking solutions, including cloud and security integration.

Extreme Networks serves diverse industries, from education to healthcare and government.

Upsides

Growing demand for AI-driven network management boosts Extreme Networks' market potential.

Expansion of 5G networks increases need for advanced networking solutions.

Rising adoption of cloud-based solutions enhances Extreme Networks' scalability and flexibility.

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