About Norm Ai
Norm Ai is the Compliance AI Platform for legal standards-based reasoning and workflow automation.
We developed the first Domain Specific Language (DSL) that fully represents regulatory requirements in AI code. Deployed through our enterprise platform, this DSL empowers Norm clients to transform workflows and enforce compliance checks at the core of their business operations.
By building and deploying Government-Grade Regulatory AI, we are setting the standard for compliance processes within the world's largest institutions and paving the way for broader deployment of AI agents in highly regulated workflows. Our rapidly expanding client base manages a combined $17 Trillion in AUM.
Our team comprises software engineers from Palantir, Google, Meta, AWS, Harvard, Stanford, and MIT, and legal engineers from Harvard Law, Stanford Law, Yale Law, Sullivan & Cromwell, Simpson Thacher, Davis Polk, Greenberg Traurig, the SEC, and FINRA.
We have secured investments from Vanguard, Blackstone, Bain Capital, Coatue, Craft Ventures, New York Life, Citi, TIAA, Larry Summers, and Marc Benioff.
This Role:
As an Engineering Manager at Norm Ai, you will lead, support, and grow a high-performing engineering team, aligning their efforts with strategic business goals. You will partner closely with technical directors, legal engineers, product teams, and executive leadership to deliver innovative compliance solutions.
You Will:
Provide people leadership and career mentorship through regular 1:1s, performance management, and development planning.
Collaborate closely with technical directors to ensure project execution aligns with strategic priorities and resource capabilities.
Facilitate team processes, remove obstacles, and promote a collaborative and high-performance team environment.
Lead hiring efforts, conduct interviews, and develop talent acquisition strategies in collaboration with technical directors and recruiting teams.
Communicate effectively with senior leadership to ensure alignment and transparency on team progress, challenges, and successes.
Regularly engage with cross-functional stakeholders to ensure your team’s work integrates seamlessly with broader organizational initiatives.
Skills & Experience - Core:
4+ years of experience as an engineering manager or similar leadership role.
Demonstrated success managing high-performing teams and developing engineers' careers.
Strong technical background – ideally in software engineering, machine learning, or AI research –enabling you to effectively collaborate with your team.
Proven ability in stakeholder management, cross-team coordination, and resolving conflicts.
Exceptional communication and interpersonal skills.
Comfortable with strategic thinking, balancing immediate delivery with long-term technical and organizational health.
Skills & Experience - Pluses:
Experience in highly regulated industries (finance, healthcare, compliance).
Familiarity with AI/ML-driven systems or regulatory technology solutions.
Experience managing teams through periods of rapid growth and scale.
What Success Looks Like
30 Days:
Build strong relationships with your team members and cross-functional partners.
Gain deep understanding of Norm Ai's technical architecture, key challenges, and organizational goals.
Clearly articulate team priorities and establish initial frameworks for team communication and operational effectiveness.
60 Days:
Effectively drive execution of significant initiatives, demonstrating improved team productivity and clarity.
Foster a strong culture of ownership, accountability, and collaboration within your team.
Actively contribute to strategic discussions, highlighting opportunities and risks clearly and proactively.
Competitive salary and equity
The base salary range for this full-time position is $235,000-$270,000 + generous early employee equity
401(k) with the highest match legally allowed
Top-tier health, dental, hospital, accident and vision insurance
Relocation reimbursement available if candidate decides to relocate to NYC
Fast-paced learning environment
We embrace a flexible hybrid model, typically in-office 3–4 days per week.
If you’re interested in the role but aren’t sure whether you’re a good fit, we’d still like to hear from you.
