Liquidity Intelligence & Forecasting
The flagship. You’ll own building a continuous, real-time monitoring and decisioning engine that watches every account and rail, forecasts cash coming in and going out, and recommends funding moves ahead of need—weighing cost and risk to find the most efficient option.
Impact: This is the platform’s flagship differentiator—real-time, network-driven liquidity management built to scale with Cobre’s payment volumes and set the industry benchmark for liquidity efficiency.
Cash Visibility & Execution Infrastructure
One live view of Cobre’s entire cash position—fiat (COP, MXN, USD) and stablecoins (USDT/USDC) together, across every bank and rail—feeding both internal executive decision-making and autonomous liquidity positioning. You’ll build the system for every balance flowing into the bank account inventory and signatory tracking as the account universe grows, expanding direct API coverage across banking partners.
Impact: Real-time, trustworthy cash data is the foundation the forecasting and decisioning engine runs on—this is what makes the rest of the platform possible.
Liquidity Risk, FX Exposure & Governance
As the platform matures, you’ll own visibility into Cobre’s FX exposure by currency and legal entity, hedge coverage, and the true cost of moving money through each currency corridor; detecting trapped cash sitting idle in low-velocity pools and accounts; scenario planning that stress-tests the liquidity plan against demand spikes and manual what-if decisions; and the audit trail and override logging that makes the engine’s recommendations explainable as it takes on more autonomy.
Impact: This is what lets Cobre scale liquidity management without scaling headcount linearly, and trust the system enough to let it act on its own.
•
Lead a product squad — engineers and data scientists partnering closely with Treasury Ops; you’re the PM driving what gets built and why.
•
Define and ship — own the full cycle from problem discovery to production. Interview Treasury, Finance, and BD stakeholders, make build-vs-buy calls on treasury management tooling, and define the metrics that prove the system works.
•
Build with an AI-native mindset — use AI tools to prototype, model, and test ideas yourself—mocking up flows, validating decision logic, or querying data—before engineering commits to building it. You provide working proofs of concept, not just requirements docs, and you expect the same builder instinct from your squad.
•
Balance phases and priorities — foundation and the flagship differentiator come first, then execution depth, then risk and governance, then autonomous execution. Prioritize ruthlessly based on what most reduces risk to our customer’s experience with our real-time payments product.
•
Partner across the org — work closely with Treasury/Revenue Operations, Data & Decision Science, Engineering, Finance, and Sales, plus external counterparts like lenders and banking partners. Translate treasury and covenant requirements into product features.
•
Stay close to the data — be comfortable in tools and systems the team builds in, understand the data and decisioning models well enough to sanity-check them, and translate DDS’s work into product and business impact.