Founding AI Product Engineer

Founding Ai Product Engineer

• Argentic is looking for an early engineering hire to help build agent-first systems for the messy receive side of B2B payments.
• This is not a generic full-stack role, and it is not a prompt-wrapper role.
• We are looking for someone deeply hands-on with modern AI systems: models, tools, agents, evals, retrieval, workflow orchestration, structured extraction, and human-in-the-loop review.
• Argentic is building a supplier-side B2B payments platform.
• Buyer-side AP systems have made it easier for large companies to initiate payments, earn rebates, and enforce preferred workflows.
• Suppliers still deal with the operational mess of receiving those payments:
• Virtual card emails and payment notices
• ACH, wire, check, card, and portal payments
• Missing or detached remittance
• PDF, email, spreadsheet, and portal data extraction
• Cash application and reconciliation
• ERP-ready posting
• Payment controls, auditability, and exception handling
• Our thesis is that B2B payments will remain many-network, many-system, and many-format.
• We are building the receive-side control layer that helps suppliers make that fragmented world tolerable now and more interoperable over time.
• What you will work on
• You will help design and build systems that turn messy payment and remittance workflows into controlled, auditable, export-ready outputs.
• This includes:
• Building agent-first workflows for payment intake, remittance capture, matching, exception review, and ERP-ready output
• Combining LLMs, deterministic business logic, workflow state, structured extraction, human review, and audit trails
• Creating eval harnesses to measure whether AI workflows are actually improving finance operations
• Experimenting with models, prompts, tool use, retrieval strategies, structured output, and orchestration patterns
• Shipping product directly with founders, customers, and design/product context close at hand
• Working across backend, integrations, data workflows, internal tools, and product infrastructure
• Helping decide what should be automated, what should be reviewed by a human, and what should remain deterministic
• What we are looking for
• Strong signals include:
• You have built LLM-powered or agentic systems beyond simple chat interfaces
• You can explain tradeoffs across model quality, latency, cost, reliability, tool use, and structured output
• You understand why evals matter and have built or used harnesses to compare prompts, models, retrieval strategies, or workflows
• You are comfortable turning messy business processes into working technical systems
• You care about reliability, observability, failure modes, review paths, and auditability
• You can move between prototype speed and production discipline
• You are curious about new AI capabilities, but practical enough to know when simpler code is better than another agent
• Relevant experience could come from fintech, payments, banking, accounting, treasury, AP, AR, payroll, tax, commerce, vertical SaaS, workflow automation, document extraction, reconciliation, data operations, finance operations, or integration-heavy products.
• You do not need to be a payments expert on day one, but you should be excited by operational complexity where correctness matters.
• This may not be the right role if:
• Your AI experience is limited to calling a model API inside a standard app flow
• You see agents as magic rather than systems that need state, tools, constraints, tests, and review paths
• You need clean requirements before making progress
• You only want to work on frontend polish or only on infrastructure
• You prefer optimizing inside a mature engineering organization over helping build the engineering culture from the ground up

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