Founding AI And Machine Learning Engineer Full Time NEW

Role: Founding AI & ML Engineer Location: New York, NY (On-site / Hybrid) Employment Type: Full-time

Company Description

Outcome-Engineered Finance for the Post-Seat Economy.

CAiDENN is architecting the world’s first Financial Processing Unit (FPU) to displace legacy ERP debt for the Fortune 2000. We are redefining enterprise finance by replacing static, seat-based “filing cabinets” with a deterministic, agentic engine that sits at the core of the business.

Managing billions in audited transaction volume for global anchors like SS&C, CAiDENN is the infrastructure layer where probabilistic AI meets the uncompromising math of a .NET 10 hardened core. We move at 10x speed using AI-native multipliers (Claude Code, Lovable) to out-produce legacy firms. At CAiDENN, we don’t build software to help people work; we build engines that own the outcome.

Role Description

As our Founding AI & ML Engineer, you will be the primary architect of the FPU’s “Intelligence Layer.” You will lead the development of our GCP-native Agentic Orchestration layer, building the brains that plug directly into our Azure-hardened calculation core.

This is a role for a builder who thrives on solving high-fidelity R&D challenges and turning them into production-grade financial controls. You will collaborate directly with the Founder to move the FPU from purely deterministic math to a future of autonomous agentic outcomes.

Key Mission Tracks (The GCP Build-Out):

• The Ingestion Airlock (PDF-to-Ledger): Engineering the agentic pipeline on GCP (Vertex AI) to transform chaotic enterprise PDF contracts into high-fidelity, structured financial data.
• Autonomous Reconciliation: Building high-trust models on GCP to perform direct reconciliation across disparate ERP, CRM, and Operational Usage sources where schemas don’t align.
• Variance & Anomaly Intelligence: Automating the month-over-month comparison of price changes using GCP-based agentic logic, generating natural language insights, and flagging institutional anomalies in real-time.

Qualifications

• AI-Native Builder: Proficiency in Machine Learning, NLP, and LLM orchestration (Mastra, LangGraph, or equivalent). You use AI agents to build systems you couldn’t build alone.
• Multi-Cloud Fluency: Expert-level experience with GCP (Vertex AI, BigQuery, GCS). You understand how to bridge a GCP intelligence layer with an Azure-based infrastructure.
• Technical Stack: Expertise in Python, and frameworks like TensorFlow, PyTorch, or scikit-learn.
• Architectural Rigor: Strong understanding of distributed systems and high-performance computing. You identify “Race Conditions” where others see “Model Hallucinations.”
• Institutional DNA: Master’s or Ph.D. in Computer Science or Data Science is preferred, but we prioritize a proven track record of shipping production-grade agents in high-stakes environments (Fintech, Trading, or Infrastructure).
• Collaborative Grit: Ability to work in a high-bandwidth, GTM environment where you prioritize outcomes over endless meetings.

DM to discuss joining our 2026 sprint.