AI Engineer

Requirements

Strong engineering fundamentals across backend systems, APIs, and cloud infrastructure. You are comfortable owning the full lifecycle of a production AI feature. Hands‑on experience building with LLMs in production, including prompt design, RAG pipelines, structured extraction, or agentic systems. Comfort working with financial or compliance‑sensitive data, where correctness and audit ability matter. A bias toward shipping; you move fast, make pragmatic trade‑offs, and iterate based on real‑world feedback.

Low ego, high ownership: you are as comfortable debugging an edge case as you are proposing a new system architecture.

• Familiarity with fintech or expense management domains.
• Prior work at an early‑stage startup or a small, high‑velocity team.

• Work on AI problems that are genuinely hard—financial data is structured, high‑stakes, and unforgiving.
• Own meaningful surface area from day one on a lean team where your decisions shape the product.
• Competitive salary and equity.
• Flexible working environment.
• A front‑row seat to building a category‑defining fintech from the ground up.

Work on AI problems that are genuinely hard—financial data is structured, high‑stakes, and unforgiving. Own meaningful surface area from day one on a lean team where your decisions shape the product. Competitive salary and equity. Flexible working environment. A front‑row seat to building a category‑defining fintech from the ground up.