Senior Software Engineer (AI)

Location: Bellevue, Washington, United States; hybrid with 3 days per week in the office

Salary: $236,000–$339,200 per year

Company

Snowflake provides a Data Cloud that processes large-scale data across global multi-cloud environments.

What you will do

• Design and scale components of the External Observability Platform across AWS, Azure, and GCP.
• Build reliable backend services for time-series data, high-cardinality metrics, distributed traces, and logs at massive scale.
• Automate infrastructure lifecycles and telemetry pipelines using infrastructure as code.
• Collaborate with Application Engineering, Security, and Customer Support to turn telemetry into actionable customer-facing insights.
• Investigate critical distributed-system failures, conduct post-mortems, and build automation to prevent recurring incidents.

Requirements

• 7–12 years of professional experience building infrastructure and backend distributed systems at scale.
• Strong programming experience with Go, C++, Java, or Rust.
• Experience deploying and maintaining hyper-scale distributed systems in public cloud environments.
• Deep knowledge of data structures, algorithms, concurrency, storage engines, distributed consensus, and networking protocols.
• Hands-on experience with Terraform or Pulumi and observability technologies such as OpenTelemetry, Jaeger, Kafka, Flink, ClickHouse, Prometheus, or Thanos.
• Strong communication, collaboration, troubleshooting, and technical project leadership skills.

Nice to have

• Experience with high-performance computing or global installations processing petabytes of telemetry daily.
• Experience building external observability tools, APIs, and analytics dashboards.
• Linux kernel tuning, eBPF-based profiling, or low-level network optimization experience.
• Experience operating cloud-agnostic infrastructure across AWS, Azure, and GCP simultaneously.

Culture & Benefits

• Work in a fast-moving, experimental engineering environment focused on challenging conventional approaches.
• Collaborate with engineering, security, and customer-facing teams on enterprise-scale infrastructure.
• Follow strict confidentiality and data security standards for handling sensitive customer information.