Applied AI Engineer
RilletSan FranciscoPosted 27 April 2026
Job Description
Applied AI 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 https://www.g2.com/products/rillet/reviews. 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.
WHO WE ARE
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.
WHO WE NEED
As an Applied AI Engineer on Rillet's AI & ML team, you'll design and ship production AI systems that transform how finance and accounting teams operate. This team sits at the intersection of LLMs, ERP workflows, and financial data, building the intelligence layer that makes Rillet fundamentally different from legacy ERP. You'll own high-impact features end-to-end, from model integration to infrastructure, and your work will be used daily by finance teams at companies like Neuralink, Kickstarter, and Windsurf.
We're an AI-native company, and we expect our engineers to bring that same mindset to how they work. If you're energized by pushing the boundaries of what AI can do in a real product context, you'll fit right in.
We're looking for teammates within commutable distance of our NYC or San Francisco offices (or willing to relocate). Team members work in-office Tuesdays and Thursdays, plus one additional flexible day.
WHAT YOU'LL DO
- Own AI features end-to-end: from designing agentic workflows and RAG pipelines to the infrastructure that runs them in production at scale.
- Work on genuinely hard problems: financial data is structured, high-stakes, and unforgiving, making it one of the more interesting domains to apply LLMs to.
- Build the evaluation frameworks and experimentation loops that turn good models into reliable, production-grade systems.
- Partner directly with product and domain experts to push the frontier of what AI can do inside an ERP, not just what's been done before.
WHO WE'RE LOOKING FOR
- 3+ years in a technical role with a strong foundation in backend systems, APIs, and cloud infrastructure
- 2+ years shipping production AI systems with real users and real stakes, not research or prototypes
- Hands-on experience with production LLM applications: RAG pipelines, agentic systems, or structured extraction
- Proficiency in Python and comfort working across the full stack to deliver end-to-end features
- Strong product instincts and a habit of thinking about user impact, not just technical correctness
- Drawn to hard, ambiguous problems and energized by building in an en ... (truncated, view full listing at source)
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