AI Platform Engineer (W2)

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. These systems must be scalable, secure, reliable, observable, adaptable, and safe for enterprise use cases.

Our group is responsible for developing core platforms and services spanning networking, agentic AI, distributed data processing, real-time analytics, and intelligent automation. These capabilities positively impact multiple existing flagship products as well as new company offerings. We are spearheading a fundamental shift in how businesses operate and manage their wired and wireless networks by building high-performance, real-time systems that can process massive volumes of network data, derive actionable insights, and enable intelligent agents to assist users or act on their behalf. As part of this group, you will continuously experiment with emerging technologies, create best-in-class networking experiences, and launch state-of-the-art software, data, and AI solutions.

Basic Qualifications:

Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related technical discipline, or equivalent practical experience.
8+ years of experience across the complete software development lifecycle, including architecture, design, coding, code reviews, testing, build processes, deployment, and production operations.
8+ years of programming experience, with proficiency in at least one general-purpose programming language, preferably Python, Java, Go, or C++.
5+ 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