You’ll be core to our product — designing, building, and operating the autonomous agents that power Causa Prima. From invoice validation and dispute resolution to cross-company negotiation and cash optimization.

What you’ll do

Agent architecture — Design the multi-agent system: agent boundaries, event contracts, orchestration patterns, and the separation between LLM reasoning and deterministic enforcement. LLMs inform; rules enforce.
Document processing pipeline — Ingestion, classification, and structured extraction from financial documents (invoices, contracts, purchase orders) using LLM-based parsing and vision models. Sandboxed processing for untrusted documents.
Validation & anomaly detection — Business rule checks, three-way matching, pricing discrepancy detection, and anomaly detection across time.
Integration framework — Gmail, Google Drive, Slack, banking APIs, crypto wallets, and accounting platforms. Auth model, credential lifecycle, data normalization.
Knowledge graph — Neo4j context graph that captures implicit business knowledge — the “why” behind decisions. Entity extraction, GraphRAG patterns, provenance tracking.
Multi-LLM strategy — Per-agent model selection, structured output contracts via Pydantic schemas, evaluation framework, fallback strategy.
Compliance & security — Agents operate within a zero-trust model. You’ll design how agents verify independently against source data, how outbound content is reviewed, and how the system prevents cascading failures from prompt injection.

What we’re looking for

3+ years experience with Python and/or TypeScript in production.
Strong systems design thinking — agent boundaries, failure modes, trust boundaries, contract evolution.
Strong interest and hands-on experience in LLM-powered systems, agent orchestration frameworks (LangGraph, LangChain, or similar), and document AI (LlamaIndex, LlamaParse, or similar).
Strong opinions about when to use an LLM vs. a rules engine vs. traditional ML — and the courage to defend them.
Experience designing data pipelines, integration architectures, or event-driven systems in production.
Security awareness — you think about what happens when untrusted input meets your pipeline.
Effective use of AI coding tools with strong review skills for LLM integration and auth code.
Interest in the finance domain — financial workflows, accounting processes, payment systems — is a strong plus.

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