Founding AI/ML Engineer

We are a pre-seed funded reg tech startup ($1.5M raised), building Carta for regulated companies. We’re creating AI agents that draft, verify, and benchmark public companies and registered fund's filings with human-level reasoning and legal defensibility.

• Multi-agent orchestration (serial parallel) using LangGraph, MCP, and PydanticAI
• Graph-based retrieval (Graph RAG) across filings, entities, and historical disclosures
• Reinforcement learning for consistency, hallucination reduction, and reward-based accuracy
• Deep integration with corporate data systems (ERP, 365, equity management) to create a single source of truth

The Role

We’re hiring a Founding AI/ML Engineer to own architecture, algorithms, and reliability.

You’ll design multi-agent systems that reason over structured unstructured data and deliver auditable, regulator-ready outputs.

This role sits at the intersection of applied research, product, and infrastructure — you’ll ship code that defines the next category of enterprise compliance software.

What You’ll Do

• Architect multi-agent systems for reasoning and verification in high-stakes regulatory workflows
• Build graph-based retrieval and long-context scaffolding for fact consistency and cross-document reasoning
• Develop evaluation and reinforcement learning frameworks to optimize accuracy and minimize hallucination
• Create domain-specific prompting and chain-of-thought patterns for corporate filings and risk disclosures
• Translate legal and financial reasoning into programmable state machines and decision DAGs
• Ship fast — from prototype to production — with full ownership over latency, reliability, and evaluation

What We’re Looking For

• 3 years in ML/AI, with strong grounding in transformer architectures, RLHF, or retrieval-augmented systems
• Experience building or scaling multi-agent architectures or graph-based reasoning systems
• Proficiency in Python (LLM frameworks, orchestration tools, cloud pipelines)
• Experience working in high-security or high-accuracy domains (finance, legal, healthcare)
• Bias toward speed, clarity, and ownership — you think like a founder, not an employee

Nice to Have

• Experience with LangGraph, PydanticAI, or custom orchestration frameworks
• Research or applied work in reinforcement learning, chain-of-thought reasoning, or graph retrieval
• Understanding of SEC filings or regulated workflows
• Advanced degree in CS, ML/AI, or equivalent depth of experience

Why Join

Competitive cash and equity comp. This is a rare chance to be at the front row seat to define a new category — turning compliance from cost center to data asset.