---
title: 'Member of the Technical Staff at Norm Ai'
canonical: 'https://feeny.ai/job/member-of-the-technical-staff-norm-ai-new-york-gyrvbwy8wrct'
type: 'job'
last_seen: '2026-11-08'
---

# Member of the Technical Staff at Norm Ai

- **Company:** Norm Ai
- **Location:** New York, NY
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-11-05
- **Last confirmed live:** 2026-11-08
- **Apply:** https://jobs.ashbyhq.com/norm/71d78164-154e-4bf2-8740-128a97a93626

## Job description

## About Norm

Norm builds AI-native professional services firms and the technology that powers them. Our mission is to help expert professionals deliver better work at greater scale. Developing the technology and the firms together lets us rethink how work gets done, how teams operate and what clients can expect. Professional judgment and experience guide what we build, while advances in the technology expand what our firms can deliver. Our shared agentic platform connects that progress across teams and services. Founded in 2023, Norm brings together experts across engineering, research, product, design and professional practice. Our legal and compliance platform serves institutions representing more than $35 trillion in combined assets under management. Norm also powers Norm Law, LLP, an affiliated AI-native law firm whose attorneys advise leading institutions on complex corporate matters.

AI Fluency: Norm prefers all team members to be fluent in AI. Successful candidates actively use AI in their day-to-day work to support thinking, creation, and problem-solving. They use it to improve the quality and speed of their work and to continuously refine how work gets done end-to-end.

Candidates should be prepared to demonstrate and discuss their AI usage throughout the interview process, including concrete examples of tools, workflows, and outcomes. We look for practical, hands-on experience, not theoretical familiarity. This Role

- Advance our multiplayer agentic harness so humans, agents, firm systems, and clients can collaborate on shared work with the right context, permissions, and accountability.
- Design multi-agent workflows using orchestration and actor models so agents can divide work, coordinate with people and other agents, and recover when plans change.
- Build shared task and state management so work moves reliably between agents, attorneys, clients, and firm systems without losing context or ownership.
- Make agents more effective across software through computer use and deep integrations with the systems a professional services firm depends on.
- Turn expert interactions into learning signals by capturing how people delegate, correct, and review work, along with the context behind their decisions.
- Build memory and continual learning systems that improve how agents support each person and the collective firm, while making it easy to adopt new training methods and frontier models.
- Improve evaluation frameworks that connect agent performance to economic outcomes, measuring the quality, cost, time, and human effort required to deliver client work.
- Build dynamic, collaborative interfaces where people and agents can work together to review documents, compare alternatives, and resolve exceptions.
- Define new ways to delegate, monitor parallel work, request input, and approve consequential actions across teams and client relationships.
- Give firm leaders a live view of operations, connecting priorities, ownership, dependencies, and progress across people, agents, and matters.
- Engineer for high-stakes collaboration with permissions, confidentiality controls, audit trails, secure execution, and reliable recovery built into the platform.
- Make legal precedent more useful to agents and apply general capabilities to demanding workflows such as due diligence, cap table reconciliation, and transactional document review.
- Bring clients into the workflow through portals and shared workspaces that connect their questions, documents, and decisions to the attorneys and agents moving matters forward.
- Push our own engineering practices forward by building with coding agents, testing new approaches to agentic development, and measuring their effect on delivery speed and software quality.
- Conduct novel AI research grounded in real professional work, publish findings, and contribute to the research community through collaboration and conference talks.

## Compensation and Benefits

Base salary: $250,000 to $400,000 per year The range displayed in this job posting reflects the minimum and maximum target for new hire salary for this position. Within the range, individual pay is determined by various factors, including job-related skills, experience, and relevant education or training. Equity: Included Benefits: 401(k) with employer match, health, dental, vision coverage, unlimited paid time off, free lunch in office daily, employee referral bonus program Relocation: For candidates needing to relocate to NYC, we provide relocation reimbursement.

Work Location Location: NYC Work model: Hybrid

To learn more about Norm, visit our [website](https://www.norm.ai).

## About Norm Ai

## Company Overview
- **One-liner**: Norm Ai builds Legal & Compliance AI agents that automate regulatory and compliance tasks by embedding law directly into AI systems.
- **Entity Type**: Private (Private Equity-backed)
- **Headquarters**: New York, New York, USA (7 World Trade Center, 39th Floor)
- **Founded**: 2023
- **Founders**: John Nay (CEO)

## Core Business
- **Primary industry/industries**: Legal Technology, Regulatory Compliance, Artificial Intelligence
- **Target customers**: Large financial institutions, asset managers, and enterprises in regulated sectors (finance, healthcare, legal). Clients include firms with a combined $20+ trillion in assets under management.
- **Mission or purpose statement**: To make compliance advice abundant and set the norms for an agentic implementation of law and policy.

## Products & Services
- **Norm Ai Platform (Regulatory AI)**: AI agents that automate compliance tasks such as risk identification, compliance checks, and regulatory report generation, while adhering to legal and regulatory requirements.
- **Supervisory AI**: A verification and oversight layer for every AI agent operating under law, ensuring compliance and governance.
- **Norm Law**: The world's first fully AI-native law firm for global institutional clients, launched in early 2026.
- **Legal AGI Lab**: The R&D arm (launched April 2026 at Stanford FutureLaw) advancing Legal AGI and the science of AI agents governed by human law.

## Market Standing
- **Valuation/Market Cap**: Not publicly disclosed.
- **Total Funding**: $136.1M raised to date.
- **Key Funding Rounds**:
  - January 2025: $48M raised from Vanguard, Blackstone, Bain Capital, Citi, TIAA, and Coatue.
  - Early 2026: Additional $50M investment from Blackstone alongside the launch of Norm Law.
- **Notable Investors/Partners**: Blackstone, Coatue, Citi Ventures, Vanguard, Bain Capital, TIAA, New York Life Ventures.
- **Growth Signals**: 
  - Trusted by institutions managing over $30T in combined assets.
  - Client base includes firms with a combined $20 trillion in assets under management.
  - 99 total employees as of mid-2026.
  - Founded in 2023 and already raised $136M+.
  - High-profile hires: Mike Schmidtberger (former Chairman of Sidley Austin) joined as Chairman of Norm Law in January 2026.
  - Senior policy advisors include Susan Dudley (former White House Regulatory Czar) and Troy Paredes (former SEC Commissioner).

## Competitive Advantages
- **First-mover in "Agentic Law"**: Pioneered the concept of embedding legal rules directly into AI agents, creating a defensible position in a nascent category.
- **Institutional Trust**: Backed by and serving the world's largest asset managers, providing a powerful network effect and credibility.
- **Dual Structure (AI + Law Firm)**: Operates both a technology company (Norm Ai) and an affiliated AI-native law firm (Norm Law), allowing it to practice law directly and encode legal judgment.
- **Supervisory AI Moat**: A verification layer that governs AI agents under law, addressing the critical societal-AI alignment problem.
- **Talent Network**: Engineers from Palantir, Google, Stripe, Meta, AWS; Legal Engineers from Harvard Law, Stanford Law, Yale Law, top law firms, and regulators.

## Strategic Focus
- **Scaling Agentic Law**: Expanding the deployment of Regulatory AI agents across the largest financial institutions globally.
- **Building the Legal AGI Lab**: Advancing long-term R&D toward Artificial General Intelligence for legal reasoning.
- **Growing Norm Law**: Recruiting world-class law firm partners and scaling the AI-native law firm for institutional clients.
- **Policy Leadership**: Convening regulators and industry leaders (e.g., U.S. Senators, SEC commissioners) to shape the norms for AI governance.

## Why Work Here
- **Mission-driven**: Work on the societal-AI alignment problem by embedding democratically-determined law into AI systems.
- **High-impact environment**: Fast-paced learning alongside experts at the intersection of law, AI, and technology.
- **Talent density**: Colleagues from top tech companies (Palantir, Google, Stripe) and top law schools/firms.
- **Compensation**: Competitive salary and equity, 401(k) with employer matching, paid parental leave, premium healthcare.
- **Work model**: Hybrid (employees work from physical offices in NYC at the World Trade Center). Relocation reimbursement available.
- **Culture**: High ownership and high trust environment. Free daily lunches, snacks, and drinks in-office. State bar fee reimbursement for legal professionals.
- **Career growth**: Opportunity to define a new category ("Legal Engineering") and work on cutting-edge AI deployment.

## Sources
1. [norm.ai](https://www.norm.ai/)
2. [norm.ai/company](https://www.norm.ai/company)
3. [norm.ai/careers](https://www.norm.ai/careers)
4. [builtin.com](https://builtin.com/company/norm-ai)
5. [cbinsights.com](https://www.cbinsights.com/company/norm-ai)

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- [Director of PR & Communications](https://feeny.ai/job/director-of-pr-communications-norm-ai-new-york-4qe3kf0sbwc3) — New York, NY
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