Settlement Operations Lead

Replenysh is building the operating system for circular supply — coordinating the movement of materials, money, and data between suppliers, carriers, recyclers, and global brands like Amazon and PepsiCo. Every transaction has multiple counterparties and settlements — buyers, sellers, service providers, freight, commissions, and more. Right now, too many of them have silent errors. We need someone who treats operational correctness like a product.

Trust is the foundation of every material network. A supplier who waits ninety days to be paid never forgets it. A buyer who receives an incorrect invoice questions every future transaction. Operational trust is not a support function at Replenysh — it is core infrastructure. Settlement reliability is the operational nervous system of the company and the foundation everything else gets built on.

• —Invoice accuracy — every buyer is billed the right amount, every time.
• —Payout timing — every seller is paid in full and on schedule.
• —Reconciliation — every transaction closes cleanly across all counterparties and settlements.
• —Exception management — anomalies get caught, escalated, and resolved before anyone calls.
• —Root cause analysis — when something breaks, you find the underlying cause and design it out.
• —Process instrumentation — dashboards, alerts, and controls that prevent regressions.

• —Precision operator with builder instincts — not a passive task executor.
• —Obsessive loop-closer. You feel personal pain when something falls through a crack.
• —When something breaks, you don’t say ‘I didn’t see it.’ You ask: ‘How could the system allow this to happen?’
• —Cracked spreadsheet user. Pivot tables, lookups, modeling — second nature.
• —You’ve probably built a spreadsheet, script, automation, dashboard, or internal tool because something annoyed you.
• —AI-native. You reach for Claude, Claude Code, ChatGPT, or scripts before doing repetitive work by hand.
• —Systems thinker. You design controls and automations, not just process steps.
• —You don’t just fix errors — you redesign systems so the same error cannot happen twice.
• —Detail-obsessed, but not slow. You move fast and check your work twice.

• —Did you prioritize correctly? Did the most consequential issues get attention first?
• —Did you find root causes, or just symptoms?
• —Did you think like an owner, or like an auditor?
• —How did you handle ambiguity? Did you create clarity from messy inputs, or wait for permission?
• —Is your proposed system actually preventive, or just reactive?
• —What did you choose to build first, and does it create leverage?
• —How clearly and concisely do you communicate?
• —Did you use AI fluently, or did you grind through everything by hand?