Applied AI Research Engineer

About Norm Ai

Norm Ai is the Compliance AI Platform for legal standards-based reasoning & workflow automation. 

We developed the first Domain Specific Language (DSL) for fully representing regulatory requirements in AI code. This DSL, deployed with our enterprise platform, enables Norm clients to transform workflows and apply compliance checks at the source of business activities.

By building and deploying Government-Grade Regulatory AI, we are setting the norms for compliance processes at the largest institutions in the world, and laying the groundwork for the deployment of AI agents more broadly in highly regulated workflows. Our client base includes firms with a combined $17 Trillion in AUM, and growing quickly. 

Our Software Engineers came from Palantir, Google, Meta, AWS, Harvard, Stanford, and MIT. Our Legal Engineers are from Harvard Law, Stanford Law, Yale Law, Sullivan & Cromwell, Simpson Thacher, Davis Polk, Greenberg Traurig, the SEC, and FINRA.

We have raised $87 million over the past 18 months from Vanguard, Blackstone, Bain Capital, Coatue, Craft Ventures, New York Life, Citi, TIAA, Larry Summers, and Marc Benioff.

This Role

As an Applied AI Research Engineer at Norm Ai, you will take a methodical and holistic approach to improving the accuracy and coverage of our automation platform. You will collaborate closely with and act as a bridge between our software engineering, legal engineering, and product teams to design and refine our AI-driven compliance solutions.

• Design and build AI-powered, enterprise-grade software to meet rapidly increasing demands.
• Regularly contribute performant and high-quality code to our production codebase that conforms to the high standards of our software engineering team. 
• Autonomously prioritize between development velocity and long-term robustness of proposed solutions, always with a ruthless propensity for action.
• Run experiments with new LLM techniques and technologies across our AI infrastructure, content processing, and regulatory workflows.
• Write prompts, iterate on accuracy, and design systems for continuous improvement.
• Develop regulatory expertise that can be used as part of our LLM workflows.

• 4+ years of experience as a Software Engineer, ML engineer, or Data Scientist.
• Strong programming skills in Python, proficiency in Docker and data storage technologies such as Postgres and Redis.
• Willingness to work with frontend technologies (Typescript, react, etc) when required.
• Experience in AI/ML infrastructure and tooling.
• Interest in becoming a regulatory domain expert and working closely with legal and regulatory professionals.
• Strong reading and writing skills.
• Strong quantitative skills that can enable a data-driven approach to problem solving.

• Experience deriving insights from PDFs and/or other unstructured or semi-structured data types
• Familiarity with the latest research in LLMs and an eagerness to adopt new model capabilities as they become available
• Background working on complex compliance or regulatory systems.

• Norm Ai Integration: Rapidly familiarize yourself with Norm Ai's existing codebase, architecture, and the unique challenges of our AI-driven compliance solutions. Within the first two weeks, we expect meaningful contributions to our production codebases.
• AI Engineering: Rapidly familiarize yourself with the data flows in Norm Ai’s compliance systems and enhance the accuracy or robustness of one of our core modules.
• Domain Expertise: Develop familiarity with the underlying regulations with which Norm works.

• Norm Ai Integration: Successfully optimize, implement, and deploy significant features that improve the accuracy and coverage of our automation platform.
• AI Engineering: Effectively lead large-scale improvements to our AI system, including runtime optimizations and accuracy improvements.
• Domain Expertise: Leverage regulatory expertise to effectively collaborate with the legal engineers and improve new and existing LLM workflows

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.