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Remote option, metro location, and broad senior engineering skillset raise candidate competition density.
Distributed systems and AI-infrastructure skills transfer across industries, though networking domain preferences add specialization.
Explicit 7+ years and 3+ years leading distributed systems plus required programming and cloud experience increase filter strictness.
Lead design and development of scalable, secure, real-time distributed systems powering AI-driven intelligent networking and agentic automation.
Own end-to-end software lifecycle for high-performance microservices, data pipelines, and AI platforms processing large volumes of network data.
Provide technical leadership, mentor engineers, and drive innovation in architecture, operational excellence, and emerging AI technologies.
Bachelor’s degree in Computer Science, Engineering, Mathematics, or related technical discipline (or equivalent experience).
7+ years software development experience including architecture, design, coding, testing, deployment, and operations.
7+ years programming experience in general-purpose languages such as Python, Java, Go, or C++.
3+ years leading design and architecture of large-scale distributed systems on cloud platforms (AWS, Azure, GCP).
Experience with real-time microservices, distributed data platforms, agentic AI systems, or network telemetry at scale.
Proven ability to lead teams technically, solve complex ambiguous problems, and deliver production-ready solutions.
Background in AI infrastructure, generative AI, or cloud-native networking systems with familiarity in technologies like Kafka, Spark, Flink, or similar.