Software Engineer, Backend; Usage & Billing Platform

Biotechnology is rewriting life as we know it, from the medicines we take, to the crops we grow, the materials we wear, and the household goods that we rely on every day. But moving at the new speed of science requires better technology.

Benchling’s mission is to unlock the power of biotechnology. The world’s most innovative biotech companies use Benchling’s R&D Cloud to power the development of breakthrough products and accelerate time to milestone and market.

Come help us bring modern software to modern science.

As a software engineer on the Usage & Billing Platform team, you will design, build, and operate the systems that power Benchling’s usage metering, rating, and billing which are foundational to how we deliver and monetize consumption-based products. Your work will enable Benchling to scale its product offerings with financial-grade accuracy and customer transparency, while shaping the technical strategy and best practices that product and platform teams rely on to instrument features and reason about cost, value, and growth.

The breadth of Benchling’s products means a one-size-fits-all approach to metering won’t work. Our platform empowers internal application teams to emit canonical usage events, define meters and aggregation windows, and model dimensions such as units, tiers, and entitlements, all natively integrated with Benchling. As an engineer on the team, you’ll own the evolution of these capabilities end-to-end: from high-throughput, low-latency ingestion and exactly-once aggregation to backfills, reconciliation, and data quality guardrails (idempotency, deduplication, lineage).

You’ll ensure usage data is trustworthy “at rest” and immediately actionable “in motion,” enabling real-time product experiences (e.g., quotas, alerts, in-app usage views) and downstream analytics.

This team also owns the Billing Platform, the source of truth for plans, pricing, discounts and credits, and invoice generation, as well as the internal APIs and tooling that make usage-based monetization consistent by default across Benchling. Team members define modeling standards and developer ergonomics for event schemas and meters, and steward interfaces to adjacent systems such as identity & entitlements, data warehousing & reporting, ERP/payment providers, and revenue recognition.

You’ll help set the bar for reliability, auditability, and compliance, partnering closely with Product, Finance, Rev Ops, and Security to ensure our platform is robust, transparent, and ready for scale.

• Design, build, and operate high-throughput usage metering pipelines (event schemas, exactly-once ingestion, windowed aggregation), including backfills, reconciliation, and strong data-quality guarantees (idempotency, deduplication, lineage).
• Develop and evolve Billing Platform primitives including plans, pricing, entitlements, discounts/credits, invoicing, as well as integrations with identity, data warehouse, ERP/payment providers; ensure auditability, compliance, and financial-grade accuracy.
• Ship real-time product experiences powered by usage (quotas, alerts, in-app dashboards) and robust observability; define SLAs and lead incident response for platform reliability.
• Partner with Product, Finance, Rev Ops, Security, and Application teams to translate business rules into meters and pricing models; validate with experiments and usage analytics.
• Improve developer ergonomics and consistency across Benchling via clear APIs/SDKs, instrumentation standards, documentation, and mentorship; drive continual improvements to team process and tooling.

• 3+ years of professional software engineering experience, ideally in SaaS and/or platform engineering.
• Proficiency in backend development and API design with Python, Go, Java, or Type Script (Benchling uses Python internally for most systems); strong data modeling skills and experience with transactional (e.g., Postgres) and analytical stores (e.g., Snowflake/Click House).
• Experience designing and operating distributed systems and event-driven/streaming pipelines (e.g., Kafka/Kinesis/Pub/Sub) plus batch processing (e.g., Spark/Flink/Beam); solid testing…