AI Principal SW Systems Engineer

Job Summary

Position: AI Principal SW Systems Engineer -

Skills: AI, Distributed Systems, Microservice, AI Infrastructure, Agentic systems

Experience: 10 to 16+ Years

Location: Bangalore or Remote

Software Engineering:

Are you energized by the opportunity to shape the future of intelligent networking, generative AI, and autonomous agentic systems? Do you want to help build highly scalable systems that process real-time network data, power intelligent experiences, and enable AI agents to reason, remember, plan, collaborate, use tools, and safely take action on behalf of users? Do you aspire to create global impact while tackling challenges at the intersection of networking, AI, distributed systems, cloud platforms, security, and real-time data processing?

Then come advance with us.

This is an incredible opportunity to work at the forefront of intelligent networking, agentic automation, cloud-native platforms, and real-time distributed systems. You will help lead the development of core platforms and services that process large volumes of network and operational data and power AI experiences across Extreme. These systems must be scalable, secure, reliable, observable, adaptable, and safe for enterprise use cases.

Come work with a team of highly talented engineers and advance with us as we build the next generation of intelligent networking systems.

Job Responsibilities

• Serve as a thought leader and forward thinker, helping define and drive an innovative technical vision across our products and platforms. Design and launch strategic capabilities spanning intelligent networking, distributed systems, real-time data processing, agentic AI, and machine learning.
• Lead the end-to-end software development lifecycle, including architecture, design, implementation, testing, deployment, and operations. Lead technical discussions and strategy while participating hands-on in design reviews, code reviews, and implementation.
• Design and build high-performance, production-ready services for next-generation real-time data and AI platforms, including scalable data pipelines, distributed microservices, agentic solutions, and integrations with networking systems.
• Mentor and develop engineers across the team, establish a clear technical direction, and foster a culture of innovation, collaboration, accountability, and engineering excellence.
• Uphold the highest standards of technical rigor and operational excellence. Build highly resilient, secure, observable, and scalable systems, and champion improvements to architecture, engineering processes, system performance, and operational readiness.

Basic Qualifications

• Bachelor's degree in Computer Science, Engineering, Mathematics, or a related technical discipline, or equivalent practical experience.
• 10+ years of experience across the complete software development lifecycle, including architecture, design, coding, code reviews, testing, build processes, deployment, and production operations.
• 10+ years of programming experience, with proficiency in at least one general-purpose programming language, preferably Python, Java, Go, or C++.
• 3+ years of experience leading the design and architecture of large-scale distributed systems, preferably on cloud platforms such as AWS, Azure, or Google Cloud.
• Experience in one or more of the following areas: real-time microservices, stream processing, distributed data platforms, cloud infrastructure, AI or agentic systems, network telemetry, or large-scale analytics.
• Experience designing systems that process high-volume, high-velocity data with stringent requirements for scalability, availability, latency, and operational reliability.
• Experience mentoring engineers, serving as a technical lead, or leading an engineering team.
• Demonstrated ability to tackle highly complex, ambiguous, or undefined technical problems and translate them into pragmatic, production-ready solutions.

Preferred Qualifications

• Master's or PhD in Computer Science, Computer Engineering, Electrical Engineering, Machine Learning, or a related discipline, or equivalent practical experience.
• Experience building highly scalable, event-driven microservices and processing large volumes of real-time operational or network data.
• Experience building generative AI or agentic systems, including tool use, planning, memory, retrieval, orchestration, evaluation, and production deployment.
• Experience developing networking, network management, observability, telemetry, cloud infrastructure, or distributed control-plane systems.
• Experience with distributed data and processing technologies such as Kafka, Spark, Flink, PySpark, MapReduce, or comparable technologies.
• Experience working with large-scale, real-world datasets and building reliable production systems that translate data into actionable insights or automated outcomes.

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