Product Manager - Traffic & Networking

Snowflake Snowflake · Data AI · CA-Menlo Park, United States · Product Management

Product Manager for Traffic & Networking at Snowflake, focusing on defining the networking strategy to support AI products and workloads, including inference, training, and vector search. This role bridges distributed systems, cloud networking, and AI infrastructure.

What you'd actually do

  1. Define the networking strategy required to support Snowflake’s AI products, including low-latency inference paths, high-throughput data pipelines, GPU-adjacent services, and elastic scaling for AI workloads.
  2. Partner with AI platform, compute, and storage teams to ensure networking capabilities meet the performance, isolation, and reliability needs of emerging AI use cases.
  3. Drive architectural decisions around traffic engineering, load balancing, service mesh, regional and cross-region routing, and failure handling in multi-cloud environments.
  4. Identify and prioritize networking innovations that improve tail latency, throughput, and cost efficiency for both traditional analytics and AI workloads.
  5. Define customer-facing networking capabilities and abstractions that make it easy for customers to deploy secure, high-performance AI workloads on Snowflake.

Skills

Required

  • Product management experience in infrastructure, networking, distributed systems, or cloud platforms
  • Strong understanding of networking fundamentals including TCP/IP, DNS, load balancing, routing, service mesh, private link and multi-cloud connectivity
  • Experience building or operating platforms that support latency-sensitive or high-throughput workloads, such as AI inference, streaming, or real-time systems
  • Ability to collaborate deeply with engineers on architectural design, performance optimization, and scalability trade-offs
  • Customer-first mindset with the ability to translate complex infrastructure challenges into intuitive product experiences
  • Excellent communication and stakeholder management skills in highly technical environments
  • Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience

Nice to have

  • Experience supporting AI/ML platforms, including inference services, model serving, or GPU-accelerated workloads
  • Familiarity with cloud networking constructs (AWS, Azure, GCP), private connectivity, and cross-region architectures
  • Experience with service mesh technologies (e.g., Envoy, Istio), traffic shaping, or network observability platforms
  • Background working with security or platform teams on zero-trust networking models

What the JD emphasized

  • network strategy to support AI products
  • latency-sensitive or high-throughput workloads