• As a Senior Full Stack Engineer on this team, you will be a technical leader responsible for building and shaping a critical part of our AI-enhanced product. • Design, build, and maintain core features across the entire stack, from our React frontend to our Python backend services. • Architect scalable and resilient systems that can handle sensitive user data and complex, AI-driven workflows with reliability and performance in mind. • Take full ownership of major features, from initial concept and technical design through to deployment and post-launch support. • Collaborate with empathy alongside our Product partners, UX Designer, and other engineers to translate user needs into elegant technical solutions. • Mentor and guide other engineers on the team, fostering a culture of technical excellence through thoughtful code reviews and knowledge sharing. • Champion best practices for testing, code quality, security, and CI/CD to ensure we're building a robust and maintainable product. • Drive projects to completion, actively identifying opportunities for improvement in our product and processes.

• Build and ship security features for North, our AI workspace platform • Develop autonomous agents that talk to sensitive enterprise data • Write and ship minimal code that runs in low-resource environments, and has highly stringent deployment mechanisms • Pulling in new tools to enhance North's security capabilities • As security and privacy are paramount, you will sometimes need to re-invent the wheel, and won’t be able to use the most popular libraries or tooling • Perform application security testing for your code to test its resilience against real-world threats

• Build and scale ML-optimized HPC infrastructure: Deploy and manage Kubernetes-based GPU/TPU superclusters across multiple clouds, ensuring high throughput and low-latency performance for AI workloads. • Optimize for AI/ML training: Collaborate with cloud providers to fine-tune infrastructure for cost efficiency, reliability, and performance, leveraging technologies like RDMA, NCCL, and high-speed interconnects. • Troubleshoot and resolve complex issues: Proactively identify and resolve infrastructure bottlenecks, performance degradation, and system failures to ensure minimal disruption to AI/ML workflows. • Enable researchers with self-service tools: Design intuitive interfaces and workflows that allow researchers to monitor, debug, and optimize their training jobs independently. • Drive innovation in ML infrastructure: Work closely with AI researchers to understand emerging needs (e.g., JAX, PyTorch, distributed training) and translate them into robust, scalable infrastructure solutions. • Champion best practices: Advocate for observability, automation, and infrastructure-as-code (IaC) across the organization, ensuring systems are maintainable and resilient. • Mentorship and collaboration: Share expertise through code reviews, documentation, and cross-team collaboration, fostering a culture of knowledge transfer and engineering excellence.

• Design, build, and maintain backend services that power Monstro’s consumer experience • Work across our stack (Python, Node.js, and Java), selecting the right tool for each problem • Build robust APIs serving mobile and web clients while integrating with financial institutions and third-party services • Architect systems that scale gracefully as our user base grows • Identify bottlenecks and implement caching strategies (Redis, CDN, application-level caching) • Optimize query performance and tune container-based applications • Design for resilience with failover strategies, retry logic, and graceful degradation • Containerize and orchestrate services using Docker and Kubernetes • Collaborate with platform teams on infrastructure decisions • Contribute to CI/CD pipelines and ensure smooth, reliable deployments • Understand and work across the full SDLC, from local development through production observability • Work with relational and NoSQL databases, partnering with data engineers on schema and data models • Build integrations with banking systems, payment processors, and financial data providers • Implement event-driven architectures and message queues where appropriate • Build systems with security as a first-class concern, including authentication, authorization, encryption, and audit logging • Ensure systems meet fintech regulatory and compliance requirements • Guide and develop junior and mid-level engineers through code reviews, pairing sessions, and technical coaching • Partner closely with frontend engineers, product managers, and designers to deliver cohesive features • Participate in architectural discussions and incident response, contributing to a culture of continuous learning and technical excellence.