Platform Engineer, Norm AI

• 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

Desirable

• 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
• 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
• 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