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 a Platform Engineer at Norm Ai, you will architect and build reliable, scalable systems that power our AI-driven compliance platform. You'll work at the intersection of infrastructure, security, and AI operations, building foundational services that enable both our platform reliability and our product teams' velocity. You'll have significant input into our technical architecture and the freedom to propose and implement improvements across our entire stack.
You Will:
Design and implement core platform services such as secure and scalable file handling, distributed job processing, and outage-resilient LLM provider integrations
Implement comprehensive observability and security controls across our platform
Create tools and processes to improve developer productivity and deployment efficiency
Establish best practices for service reliability, testing, and documentation
Mentor other engineers on infrastructure and platform development
Skills & Experience - Core
4+ years of experience as a platform/backend engineer (or other similar role)
Strong proficiency in developing cloud-native containerized applications in at least one programming language commonly used for backend development (e.g., Python, Java, Rust, C++, etc.). We primarily use Python.
Track record of building reliable and scalable backend systems
Proficiency with data storage technologies such as PostgreSQL and Redis
Experience with observability tools such as Datadog or OpenTelemetry
Comfort with at least one of the major cloud providers (AWS, GCP, Azure)
Comfort with designing and maintaining CI/CD pipelines using tools like Github Actions
Skills & Experience - Pluses
Experience in AI/ML infrastructure and tooling
Background working on complex compliance or regulatory systems
Familiarity with serverless architectures
Familiarity or experience navigating common Enterprise requirements such as SAML, SSO, 17a-4, etc.
What Success Looks Like - 30 Days
Norm Ai platform onboarding: Rapidly familiarize yourself with Norm Ai's existing infrastructure, architecture, and the unique challenges of our AI-driven compliance solutions.
Architectural analysis: Identify key areas for improvement in existing foundational services and other aspects of Norm Ai’s architecture.
Monitoring & Alerting: Implement some essential improvements to our monitoring and alerting systems to provide visibility into the health and performance of our infrastructure.
What Success Looks Like - 60 Days
Improve end user experience: Based on pain points you observe over the first few weeks, design and implement an enhancement to a core platform service, such as improving the efficiency of our distributed task queue for compliance checks.
Documentation & best practices: Contribute to internal documentation by creating or significantly improving documentation for a key platform component in a way that helps both engineers’ and their AI coding tools better contextualize their understanding of the codebase.
What Success Looks Like - 90 Days
Enhance platform scalability: Dive deep into the code for our DSL execution engine and propose a redesign that enhances its scalability by breaking the execution into smaller atomic chunks.
Mentorship & knowledge sharing: Begin mentoring other engineers on best practices by leveraging your years of experience in other roles in a way that improves their productivity, enhances their understanding, and fosters better team collaboration.
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.
