Customer Support Engineer

What We Do

Rillet serves accounting and finance teams. Our customers are the financial brains of their companies. Our job is to help them run the numbers with impossible speed, accuracy, and insight.

Rillet is an AI-native ERP that can drive a zero-day close. We are different because of our unified source-of-truth data model, hundreds of best-in-class native integrations (Stripe, Ramp, Salesforce, etc), automated & auditable workflows, multi-entity consolidation, and quickly expanding army of specialized AI agents (e.g., accrual, audit, P&L flux, board decks, etc). These earn us a consistently perfect customer satisfaction score.

High-growth AI customers like Mercor, and Function Health love our ship velocity, because their financial stack needs to scale as quickly as they do.

This huge market is ours to take. We have raised $100M from leading investors (including Sequoia, a16z, Iconiq, Oak HC/FT, and First Round) to help everyone run their numbers at the speed of AI.

Rillet’s pace is not for everyone. Intelligence is table stakes. To succeed here, you need extreme speed, agency, and flexibility.

Successful Rilleteers do not wait for assignments. They internalize a mission, design a strategy, and bring back results that are better, faster, and more creative than a manager could have asked for.

Work revolves around our customers. Successful Rilleteers are energized by delivering the most important things, even those that weren’t in the original plan.

In this role, you do not need to be an accountant. But you do need to appreciate the value that our customers can create for their own company when we equip them with the perfect financial tools. Successful Rilleteers love powering the financial core of the world’s fastest-growing companies.

Rillet's support function is new and being built intentionally — and we're building it to scale through engineering, not just headcount. You'll join as one of our first Customer Support Engineers: a hybrid role that combines front-line customer problem-solving with the technical work of building the tools, automations, and AI-assisted workflows that make support fast, accurate, and scalable.

On any given day you'll be resolving real customer issues and building the systems that resolve the next hundred. You'll respond to inbound questions, triage bugs, and get customers unblocked quickly — then turn what you learn into knowledge base content, better ticket routing, AI agent improvements, and internal tooling that makes the whole team more effective. You care about fast, accurate resolution, and you find both the support craft and the engineering behind it energizing.

This is a role for someone who thinks beyond closing tickets one at a time. You see a repeated question and want to automate it away. You see a manual triage step and want to build a workflow for it. You want to compound your impact over time, not just keep pace with volume.

We're looking for teammates who value in-person collaboration and are within commutable distance of our San Francisco (preferred) or NYC offices (or willing to relocate). Team members are required to work in-office Tuesdays and Thursdays, plus one additional flexible in-office day. Certain roles may require additional in-office time based on function.

• Resolve inbound support tickets across question types — general knowledge, bug triage, and data requests — via omni-channel support, communicating clearly and professionally in async channels with a consistent, helpful tone.

• Triage and elevate issues to Customer Success or Engineering with enough context that handoff is seamless, and flag gaps in playbooks and escalation protocols when you find them.

• Build AI-assisted workflows that automate manual support processes — ticket categorization, response drafting, knowledge retrieval, routing, and enrichment.

• Develop internal tools and integrations that scale support execution, connecting support tooling (e.g., Pylon, Linear), the product, and the data warehouse.

• Contribute to and continuously improve the internal knowledge base — documenting resolutions, product behavior, and edge cases, and turning repeated…