Software Engineer, Dev Tools

Responsibilities

• Build and operate cloud development environments and execution platforms for engineers and AI agents.
• Scale Kubernetes-based worker pools, control planes, and APIs for parallel and asynchronous workloads.
• Improve AirDev validation so engineers and agents can test changes quickly before CI.
• Strengthen source-control and code-review systems as PR volume, automation, and concurrency grow.
• Improve developer workflows across build, test, dependency management, and polyglot monorepo tooling.
• Diagnose production issues across distributed systems, networking, storage, and orchestration.
• Set technical direction and make high-stakes architectural decisions with significant ambiguity.
• Mentor engineers on the team and raise the quality bar through code review and design feedback.

Requirements

• 2-4+ years of industry experience with bachelor’s and/or Master’s degree, preferably in CS, or equivalent experience.
• Experience leading and shipping large scope technical projects in collaboration with multiple experienced engineers.
• Full-cycle developer with strong ownership and experience building and operating high-scale, distributed systems across the full software life cycle.
• Familiarity with container and orchestration technologies such as Docker and Kubernetes.
• Excellent communication skills; able to explain complex infrastructure tradeoffs to engineers at all levels and drive cross-team alignment without formal authority.
• Strong problem solver with solid debugging skills.
• Passionate about developer productivity and making developer lives better.
• Experience building systems that run reliably at scale on AWS, including EKS, EC2, EBS, and cloud networking (VPCs, load balancers, VPN tunneling).
• Platform thinking: built infrastructure that other teams build products on top of, with focus on reliability, observability, clear contracts, and graceful failure modes.
• Treat infrastructure spending as a first-class concern; driven meaningful cost reduction through architectural changes.
• Go, Python, or similar server-side languages.

Nice-to-Haves

• Developer environments, remote development platforms, or sandboxed workload execution.
• Infrastructure for AI agents or asynchronous compute workloads.
• CI/CD, integration testing, build systems, or pre-submit validation.
• Git, GitHub Enterprise, source-control infrastructure, or large-scale repository hosting.
• Code-review systems, policy enforcement, code ownership, or automated review tooling.
• Kubernetes operators, workload scheduling, autoscaling, resource isolation, or capacity management.
• Bazel, monorepo tooling, dependency management, or polyglot build infrastructure.
• Platform APIs, control planes, worker pools, caching systems, or distributed queues.
• Authentication, authorization, secrets management, or secure workload execution.
• Infrastructure cost optimization and capacity planning.