Senior Software Engineer - Infrastructure

Responsibilities:

• Build and maintain data pipelines for batch and streaming that process 3B+ daily events. Reliability and cost matter as much as throughput.
• Work on network infrastructure service connectivity, internal networking abstractions, and ensuring secure, reliable communication across our platform services.
• Own pieces of ML pipeline infrastructure: data ingestion, feature pipelines, and model serving infra that support our recommendation and personalization systems.
• Work on platform problems: container orchestration, infra-as-code, and internal abstractions that let product teams move without depending on infra for every deploy.
• Set up and improve our observability stack. Define SLIs, own alerts, and reduce MTTR. If something breaks, we want to know before users do.
• Contribute to CI/CD reliability: faster builds, cleaner rollouts, fewer incidents at deploy time.
• Contribute to internal AI tooling building or integrating tools that improve developer productivity and automate repetitive infra and data workflows.

Requirements:

• 2-5 years in backend or infrastructure engineering, with production experience, not just side projects.
• Strong Python; you write code that runs in production, not just automation scripts.
• Real experience with distributed data processing and streaming systems in a production environment.
• Hands-on with container orchestration and infra-as-code tooling.
• Familiarity with observability tooling, metrics, logs, and traces.
• Some understanding of ML pipelines; you don't need to be an ML engineer, but knowing how data flows from raw to model matters here.

Good to have:

• Experience with real-time streaming architectures.
• Exposure to ML infrastructure, feature stores, or data governance.
• Prior work in a consumer product company where data volumes are high and latency budgets are tight.
• Contributions to open-source infra or data tooling.