About the role
About Traversal Traversal is the AI Site Reliability Engineer (SRE) for the enterprise—already trusted by some of the largest companies in the world to troubleshoot, remediate, and even prevent the most complex production incidents. Our mission is to free engineers from endless firefighting and enable them to focus on creative, high-impact work. Our roots remain deeply embedded in AI research, and we’re channeling that scientific rigor and creativity into building the premier AI agent lab for the enterprise. Hence, what we’re proudest of is assembling the most talented yet nicest group of individuals, including researchers from MIT, Harvard, and Berkeley, to world-class engineers from industry: Citadel Securities, Cockroach Labs, Datadog, DE Shaw, ServiceNow, Glean, Perplexity, Pinecone, and more, to take on one of the hardest problems for AI to solve. Without the entire team, none of this would be possible.
The Role As a Full-Stack AI Engineer at Traversal, you’ll play a key role in designing and building the core product surfaces powered by our AI Site Reliability Engineer. This role is ideal for engineers who enjoy owning complex systems end-to-end—from user interface through backend services and infrastructure. You’ll help translate advanced AI capabilities into reliable, production-grade product experiences used by engineers operating large-scale systems. The right person for this role combines strong product intuition with deep engineering judgment and is comfortable working across the stack, from distributed systems and data pipelines to highly interactive front-end applications. You’ll partner closely with product, AI researchers, and infrastructure engineers to shape the architecture of the platform and build features that enable real-time incident detection, root cause analysis, and automated remediation across complex production environments.
Responsibilities Product Ownership: Drive end-to-end development of core product capabilities, translating AI-driven insights into intuitive workflows that empower engineers and reduce cognitive load. Technical Architecture: Design scalable system architectures spanning frontend, backend services, and data infrastructure to support real-time observability and automated operations. API & Platform Development: Design and implement high-performance APIs and service layers that power the product and enable seamless integration between AI systems, backend services, and the user interface. User Experience: Build highly interactive interfaces for exploring operational data, rapidly iterating with users to refine product workflows and usability. Data Systems: Design efficient strategies for storing, processing, and retrieving large-scale operational data using technologies like PostgreSQL, Redis, and distributed systems. AI Integration: Collaborate with AI engineers and researchers to operationalize model outputs in production systems, building reliable pipelines, authentication systems, and platform abstractions that enable AI-powered features. Technical Leadership: Help shape engineering best practices, influence technical direction, and raise the bar for system design, performance, and maintainability across the codebase.