About Traversal

Traversal is the AI Site Reliability Engineer (AI SRE) for the enterprise.

Production complexity was already outpacing what engineering teams could manage manually, and AI-generated code is accelerating that gap. Traversal is built for that challenge, autonomously understanding and reasoning across even the largest, most complex production environments to diagnose, fix, and prevent incidents. Our mission is to free engineers from endless firefighting and give them more time to focus on creative, high-impact work.

Today, Traversal operates in mission-critical environments at some of the world’s largest enterprises, including PepsiCo, Nubank, Harvey, and DigitalOcean. Our roots remain deeply embedded in AI research, and we’ve brought together researchers from institutions including MIT, Harvard, Berkeley, Columbia, and Cornell with world-class technical staff and operators from companies like Google, Meta, Datadog, ServiceNow, and Citadel Securities to take on one of the hardest problems for AI to solve. Traversal is backed by Sequoia Capital, Kleiner Perkins, Redpoint Ventures, and Khosla Ventures.

The Role

As a Cloud Infrastructure Engineer on Traversal’s Infrastructure team, you’ll design, secure, and operate the core systems that power Traversal’s AI products. We already serve Fortune 50 enterprises with large-scale, multi-tenant environments, BYOC deployments, and SOC 2 Type II controls, and we’re rapidly scaling.

You’ll focus on the building blocks of our Terraform-defined infrastructure and Kubernetes environments, while supporting the complex needs of operating the highly-available, highly-resilient, and cost-efficient platform that supports the Traversal AI SRE agent.

This is a senior, high-impact role: you’ll own foundational systems, work across AWS-native infrastructure, cloud networking, Kubernetes environments, Terraform, Helm, Python, and more, shaping how enterprise AI reliability is built and scaled.

Responsibilities

System Design & Architecture: Design scalable, reliable infrastructure for AI workloads, inference, data pipelines, and agentic workflows

CI/CD: Build and deliver best-in-class developer experience and software development lifecycle tooling for our growing engineering team

Autoscaling: Scale on real signals (queue lag, in-flight requests, latency); add burst capacity and safe drains

Infrastructure as Code: Evolve Terraform+Helm for multi-environment deployments, secrets, policy-as-code, and workload identity

Observability: Build and deliver end-to-end visibility into our infrastructure, systems, and applications, and connect it to Traversal’s AI SRE agent for self-driving production

Security: Partner with our cloud security lead to improve Traversal’s security and compliance posture, implementing least privilege principles, JIT access workflows, default-deny egress, auditability, and policy-as-code

Requirements

7+ years of experience at technically rigorous companies or teams

Proven experience operating cloud and Kubernetes native infrastructure and applications at scale with >99.9% availability

Demonstrated hands-on experience with AWS, EKS, Terraform, Helm

Experience designing idempotent systems (outbox, dedupe keys, safe replay)

Incident response, chaos testing, capacity planning

Strong debugging skills across infrastructure, compute, network, runtime, storage, and auth layers

Nice to Have

Service mesh (Envoy/Istio), Cilium/eBPF

GPU workload operations, inference servers, token streaming gateways

Production experience building and maintaining systems in Python, Rust, and TypeScript

Data governance (PII discovery/redaction), lineage, tokenization

Experience designing, implementing, and deploying cross-region active/active architectures

Familiarity with other cloud providers (GCP, Azure, Oracle Cloud)

Compensation

We offer competitive compensation, startup equity, health insurance, and additional benefits. The U.S. base salary range for this full-time, in-person role in New York is $175,000–$300,000, plus equity and benefits. Our salary ranges are based on location, level, and role. Individual compensation is determined by experience, skills, and job-related knowledge.