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Norm

Member of the Technical Staff

New York, United States

Location
New York, United States
Work
Hybrid
Employment
Full-time
Level
Lead / staff
Function
Engineering
Pay
$250K – $400K a year (read from the ad)
Posted
4 days ago

Pay and the market here

The top of this role’s range, $400K a year, is 43% above the median of $280K for lead / staff engineering jobs in New York (middle half $240K – $331K, 674 jobs that state pay).

3,780 engineering jobs open in New York: 12% remote, 727 posted in the last 30 days.

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About the role

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.

Source

Posted by Norm on their own hiring page, jobs.ashbyhq.com. OptiTalent shows it as published, read 09 Nov 2026 15:55 UTC; the original is the reference.

View the original ad ↗

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