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Principal Software Engineer – (Gen AI, Big Data) (10026) Seattle. WA | San Jose, CA | Salem, NH | Raleigh, NC

Extreme Networks

Salary not specified
Sep 30, 2025
Seattle, WA, US • San Jose, CA, US • Raleigh, NC, US • Salem, NH, US
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Extreme is looking to innovate with Generative AI and build ground-breaking products that define the future of AI-driven network management by tackling challenges at the forefront of Artificial Intelligence.

Requirements

  • 10+ years of experience across the full software development lifecycle including design, coding, reviews, testing, deployment, and operations
  • 5+ years of experience with distributed Big Data and ML platforms such as Spark, Lakehouse, Debezium, Kafka, Flink, or Hudi
  • Hands-on experience building Generative AI solutions such as RAG, AI Agents, and LLM fine-tuning in production
  • Experience working with Graph ML and Graph technologies such as GNNs
  • Strong track record of end-to-end solution ownership, from design through production scaling
  • 5+ years of experience deploying large-scale solutions on cloud platforms such as AWS, Azure, or GCP
  • Proven ability to solve highly complex, ambiguous, cross-domain problems with measurable business impact

Responsibilities

  • Provide technical leadership and vision for large-scale distributed systems, ML platforms, and next-generation data infrastructure
  • Lead the design, architecture, and delivery of end-to-end solutions across the full SDLC, spanning development, testing, deployment, and operations
  • Drive innovation in Big Data, Generative AI, and Graph ML by translating emerging technologies into production-ready solutions
  • Architect scalable microservices and real-time inferencing systems leveraging modern ML infrastructure such as AI Agents, MCP, ML Inference, and LLM Gateway
  • Mentor and grow engineering teams, set technical direction, and foster a culture of engineering rigor, collaboration, and operational excellence
  • Champion best practices for building resilient, secure, and high-performance systems, optimized for scale and reliability

Other

  • Degree in Computer Science, Mathematics, or a related field
  • MS or PhD in Computer Science, Machine Learning, or a related discipline
  • Experience with sensitive or streaming data pipelines, including real-time compliance and governance controls