Extreme Networks Logo

Extreme Networks

Senior AI/ML Engineer – Generative AI & Autonomous Agents (9746)

Posted 7 Days Ago
Be an Early Applicant
Hybrid
Toronto, ON
Senior level
Hybrid
Toronto, ON
Senior level
As a Senior AI/ML Engineer, you'll design, develop, and implement AI-native systems, focusing on generative AI and multi-agent workflows to enhance network design and optimization.
The summary above was generated by AI

Over 50,000 customers globally trust our end-to-end, cloud-driven networking solutions. They rely on our top-rated services and support to accelerate their digital transformation efforts and deliver unprecedented progress. With double-digit growth year over year, no provider is better positioned to deliver scalable outcomes than Extreme.


Inclusion is one of our core values and in our DNA. We are committed to fostering an inclusive workplace that embraces our differences and creates an atmosphere where all our employees thrive because of their differences, not in spite of them.


Become part of Something big with Extreme! As a global networking leader, learn why there’s no better time to join the Extreme team.


Senior AI/ML Engineer – Generative AI & Autonomous Agents


Introduction


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.

Extreme Networks, Inc. (EXTR) creates effortless networking experiences that enable all of us to advance. We push the boundaries of technology leveraging the powers of machine learning, artificial intelligence, analytics, and automation. Over 50,000 customers globally trust our end-to-end, cloud-driven networking solutions and rely on our top-rated services and support to accelerate their digital transformation efforts and deliver progress like never before. For more information, visit Extreme's website or follow us on Twitter, LinkedIn, and Facebook.


We encourage people from underrepresented groups to apply. Come Advance with us! In keeping with our values, no employee or applicant will face discrimination/harassment based on: race, color, ancestry, national origin, religion, age, gender, marital domestic partner status, sexual orientation, gender identity, disability status, or veteran status. Above and beyond discrimination/harassment based on “protected categories,” Extreme Networks also strives to prevent other, subtler forms of inappropriate behavior (e.g., stereotyping) from ever gaining a foothold in our organization. Whether blatant or hidden, barriers to success have no place at Extreme Networks.

Top Skills

Autogen
AWS
Azure
Docker
Faiss
Generative Ai
Haystack
Langchain
Llm-Based Applications
Multi-Agent Systems
Pinecone
Python
Semantic Kernel
Weaviate

Similar Jobs

Yesterday
Remote
Ottawa, ON, CAN
Mid level
Mid level
Big Data • Cloud • Healthtech • Software • Big Data Analytics
Software Engineers at Veeva will design, implement, and deliver cloud-based features while mentoring junior developers and ensuring code quality.
Top Skills: AspectjGitGradleHibernateJavaJenkinsJmsJunitLinuxLog4JMockitoMySQLSpringTomcat
Yesterday
Remote
Toronto, ON, CAN
Junior
Junior
Big Data • Cloud • Healthtech • Software • Big Data Analytics
Join the team at Veeva Systems as a Full-Stack Software Engineer, collaborating to build innovative life sciences applications. Participate in the SDLC, working closely with product managers and QA engineers while leveraging front-end and back-end technologies.
Top Skills: AngularJavaJavaScriptJssMs Sql ServerMySQLOracleReactSassVue
Yesterday
Remote
Ottawa, ON, CAN
Senior level
Senior level
Big Data • Cloud • Healthtech • Software • Big Data Analytics
Join Veeva Systems as a Senior Software Engineer to develop innovative full-stack applications in the life sciences sector, utilizing advanced front-end and back-end technologies, while collaborating with cross-functional teams.
Top Skills: AWSJavaJavaScriptJssMs Sql ServerMySQLOracleReactSassSpring

What you need to know about the Montreal Tech Scene

With roots dating back to 1642, Montreal is often recognized for its French-inspired architecture and cobblestone streets lined with traditional shops and cafés. But what truly sets the city apart is how it blends its rich tradition with a modern edge, reflected in its evolving skyline and fast-growing tech industry. According to economic promotion agency Montréal International, the city ranks among the top in North America to invest in artificial intelligence, making it le spot idéal for job seekers who want the best of both worlds.

Key Facts About Montreal Tech

  • Number of Tech Workers: 255,000+ (2024, Tourisme Montréal)
  • Major Tech Employers: SAP, Google, Microsoft, Cisco
  • Key Industries: Artificial intelligence, machine learning, cybersecurity, cloud computing, web development
  • Funding Landscape: $1.47 billion in venture capital funding in 2024 (BetaKit)
  • Notable Investors: CIBC Innovation Banking, BDC Capital, Investissement Québec, Fonds de solidarité FTQ
  • Research Centers and Universities: McGill University, Université de Montréal, Concordia University, Mila Quebec, ÉTS Montréal

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account