Bengaluru, India
AI-Staff/Principal Software Systems Engineer-Gen AI - Machine Learning - Graph ML - Big Data - 10030
Extreme Networks · Bengaluru · India
Posted: 14/7/2026 · Last checked: 11/10/2026
Job description
Quoted in full from Extreme Networks's job posting. Gavroche does not edit it.
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.
Position: AI-Staff/Principal Software Systems Engineer-Gen AI, Machine Learning, Graph ML, Big Data
Experience: 8 to 18 Years
Position type: Full-time
Location: Bangalore/Remote
Our AI Core group is pioneering platforms and solutions for Generative AI, including AI Agents, RAG, Knowledge Bases, Data Mining, Anomaly Detection, and LLM fine-tuning. These innovations power flagship Extreme products while enabling entirely new offerings. Together, we are driving a fundamental shift in how businesses manage networks by building intelligent, high-performance multi-agent systems that perceive, learn, and act in real time. At Extreme, innovation is not just encouraged, it is expected. Advance with us and help shape the future of network intelligence.
- Degree in mathematics/computer science or related discipline.
- 8+ years of experience in the complete software development lifecycle including design, coding, code reviews, testing, build processes, deployments and operations.
- 6+ years of experience in Python with an in-depth knowledge of its advanced features and libraries.
- Expertise in designing RESTful APIs with hands-on experience with technologies such as FastAPI.
- Proficient in Docker, Kubernetes, and modern CI/CD practices.
- 4+ years of experience in leading the design and architecture of large distributed systems preferably on cloud platforms (e.g., AWS, Azure, Google Cloud).
- Experience as a mentor, tech lead or leading an engineering team.
- BE/MS or PhD in Computer Science or equivalent experience in ML.
- Experience working with ML technologies (PyTorch, Sagemaker, Triton, TensorRT, etc.).
- Experience with NoSQL and document databases.
- Proven ability to handle big data, optimize workflows, and improve system performance.
- Come work with a team of highly talented engineers, and advance with us to achieve new heights every day!
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.
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