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Snowflake is seeking a Product Manager to own the product vision and roadmap for traffic and networking infrastructure that powers the company's data and AI platform at global scale. This role sits at the intersection of distributed systems, cloud networking, and AI infrastructure, with responsibility for defining how Snowflake delivers secure, reliable, and high-performance connectivity across multi-cloud environments.
Key responsibilities include defining Snowflake's networking strategy to support AI products—including low-latency inference paths, high-throughput data pipelines, GPU-adjacent services, and elastic scaling for AI workloads. You will partner with AI platform, compute, and storage teams to ensure networking capabilities meet performance, isolation, and reliability needs of emerging AI use cases. You'll drive architectural decisions around traffic engineering, load balancing, service mesh, regional and cross-region routing, and failure handling.
The role requires identifying and prioritizing networking innovations that improve tail latency, throughput, and cost efficiency for both traditional analytics and AI workloads. You will define customer-facing networking capabilities and abstractions that make it easy for customers to deploy secure, high-performance AI workloads on Snowflake, while improving observability and diagnostics for network performance.
You'll partner closely with security teams to ensure networking features align with enterprise requirements for isolation, encryption, access control, and zero-trust architectures. This is a cross-functional leadership role requiring you to drive execution across infrastructure, AI, security, and go-to-market teams, communicate complex trade-offs to senior leadership, and translate infrastructure challenges into intuitive product experiences.
Ideal candidates have 2+ years of product management experience in infrastructure, networking, distributed systems, or cloud platforms, with strong understanding of networking fundamentals (TCP/IP, DNS, load balancing, routing, service mesh, private link, multi-cloud connectivity). Experience building or operating platforms supporting latency-sensitive or high-throughput workloads (AI inference, streaming, real-time systems) is essential. A Bachelor's degree in Computer Science, Engineering, or equivalent practical experience is required. Bonus qualifications include experience with AI/ML platforms, cloud networking constructs (AWS, Azure, GCP), service mesh technologies (Envoy, Istio), and zero-trust networking models.
