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Snowflake's Billing & Payments Platform team builds the central data repository and infrastructure for customer resource consumption, revenue processing, invoicing, and reporting. This system powers Snowflake's business and serves as a reference pattern for customers building on Snowflake.
As a Senior Software Engineer on this team, you will own medium-sized projects end-to-end from design through launch and operation, and contribute as a key engineer on large, multi-team initiatives. You will build federated, distributed billing systems that meter, rate, and invoice usage across every Snowflake service, all running on Snowflake's own product. You'll shape billing strategy for AI products in partnership with Cortex AI, Intelligence, and Apps teams—including token-based inference, agent workflows, and AI-native subscriptions.
The core challenge is a distributed systems problem: real-time usage metering across every cloud and region, supporting an evolving catalog of pricing models for Cortex AI and the broader agentic AI portfolio. Systems must meet strict requirements for accuracy, auditability, and low-latency processing.
Key responsibilities include: owning reliability and correctness through on-call participation and systemic fixes to monitoring and quality; becoming the go-to expert for one or more billing components (metering, rating, invoicing, contracts, payments, threshold billing, fraud, or reporting) and mentoring other engineers; using AI as a first-class collaborator in development, code review, debugging, and on-call triage via Cortex Code CLI and Snowflake Intelligence; and partnering cross-functionally with Product, Finance, GTM Systems, Growth, Trust, and Legal to translate business intent into reliable, auditable systems.
This is a deeply cross-functional role with daily partnership across Product, Finance, Legal, Growth, Go-to-Market Systems, Snowsight UI, Cortex AI, and product engineering teams.
**Requirements:**
- 7+ years of professional software engineering experience building and supporting large-scale, production distributed systems
- Bachelor's or Master's degree in Computer Science, a related technical field, or equivalent practical experience
- Strong fundamentals in distributed systems: consistency, fault tolerance, idempotency, exactly-once processing, queueing, and stream/batch data pipelines
- Strong fundamentals in databases and data modeling—SQL fluency, schema design, performance tuning, and understanding of operational realities of large-scale data systems
- Proficiency in one or more of Java, Scala, Python, or Go, and engineering practices that make systems easy to operate at scale (testing, observability, CI/CD, incremental rollout)
- Demonstrated ability to independently design, spec, schedule, and deliver medium-sized projects with quality, and to contribute as a strong individual contributor on larger, multi-team efforts
- Track record of owning reliability for what you build—participating in on-call, debugging production issues across unfamiliar areas, and driving systemic fixes rather than one-off patches
- Excellent communication skills and collaborative working style; comfort operating across engineering disciplines and partnering with non-engineering stakeholders in Finance, Product, GTM, and Legal
- Curiosity about and hands-on experience with AI as a builder's tool, and interest in shaping commercial models for AI products
**Bonus qualifications:**
- Prior experience in billing, payments, metering, revenue, or financial systems at a SaaS or cloud company
- Experience with fraud detection, abuse mitigation, or trust/safety systems in a usage-based product
- Experience designing or evolving pricing models for AI/ML products (inference, fine-tuning, agentic workloads)
- Experience building on Snowflake or comparable cloud data platforms (Snowpark, Streams/Tasks, Iceberg, Streamlit, Cortex)
- Contributions to internal AI developer-productivity tooling, agentic skills, or Cortex Code workflows
