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 Backend AI Engineer at Traversal, you’ll play a key role in designing and building the core systems behind our AI site reliability engineer, the infrastructure that enables real-time incident detection, root cause analysis, and automated remediation in some of the most complex production environments. You’ll work closely with our AI and infrastructure teams to productionize novel AI agent architectures and machine learning algorithms, develop high-performance inference APIs, and build internal observability tooling. Your work will span ingesting and reasoning over logs, metrics, and traces at scale, optimizing systems across hybrid SaaS and on-prem deployments, and supporting mission-critical reliability for global enterprises.
Responsibilities Backend System Design & Architecture : Lead the design and implementation of scalable, robust backend systems to support AI agents and observability tools. API Development : Design and implement high-performance APIs to enable seamless communication between backend systems and frontend interfaces. Data Management : Ensure efficient data storage, retrieval, and processing, leveraging technologies like PostgreSQL, Redis, or others. AI Integration : Collaborate with AI engineers to integrate AI-driven insights and solutions into backend systems, and take ownership of API authentication and authorization frameworks. Performance Optimization : Monitor, optimize, and scale backend services to handle high volumes of data while ensuring low-latency performance. Collaboration : Partner with frontend engineers, AI researchers, and other teams to ensure a seamless, high-performance user experience. Mentorship : Provide technical leadership and mentorship to junior engineers, helping to grow a strong backend engineering team.