Software Engineer | Cloud Foundations

Position Overview The Software Engineer (Cloud Foundations) will work on core product systems using Kubernetes, Go, and Python. This role emphasizes end-to-end ownership, from concept to observability, across the stack. We use Terraform for repeatable, safe, infrastructure-as-code installations, including our bring-your-own-cloud (BYOC) offering. The ideal candidate values deep troubleshooting and holistic system ownership. The role involves hands-on use of industry-standard tools, containers, Kubernetes, Terraform IaC, and CI/CD with guardrails. You will practice debugging beyond local environments. Optional stretch work on areas like async jobs, ingress, or orchestration is available with senior engineers. Role and Responsibilities This role offers hands-on experience within small, collaborative Platform and Infrastructure teams, with projects aligned with our actual shipping processes. The role involves several key responsibilities and learning areas. Candidates will apply and understand Kubernetes fundamentals, such as Deployments, Services, reading cluster state with kubectl, logs, and resource limits, including small manifest or Helm chart changes under review. They will contribute to our Go or Python services through backend development, focusing on bug fixes, test implementation, developing small Command Line Interface (CLI) subcommands, or adding features behind a flag. The initial focus may not be on developing new controllers. Candidates will also gain exposure to Infrastructure as Code (IaC) by improving Terraform module variables or documentation, addressing environment drift in development or staging, or adding validation. Customer install scenarios are often simulated in a sandbox. A core component is Cloud Provisioning and Operations, where candidates learn the differences between our SaaS and customer-deployed infrastructure. Potential work includes improving installation documentation, enhancing diagnostics scripts, or developing internal tooling for customer clusters. They will also build essential Observability Practices by adding metrics, log fields, or trace spans, connecting them to dashboards, and documenting changes with short runbook notes. For stretch opportunities, which will involve pairing with and review by a Staff Engineer, candidates might work on a queue consumer, managing retry/idempotency logic, or building related admin tooling. They may also implement small ingress-related changes or touch upon emerging areas like proxying, task queues, and orchestration as we expand our cloud offerings. Throughout the experience, the candidate will practice owning a slice of work: clarifying requirements, implementing the solution, validating it in a cluster, and anticipating potential failure points—all within an appropriate intern scope. This involves writing and testing software, analyzing logs and dashboards, and cross-functional collaboration. Success will be measured by learning velocity, effective communication, and the contributions shipped, not by carrying sole responsibility for large-scale operations like regional failover. Required Skills and Experience Pursuing a B.S. (or equivalent) in Computer Science, Computer Engineering, Electrical Engineering, or a related discipline, or demonstrable equivalent depth from projects and coursework Solid computer science fundamentals (data structures, algorithms, and how programs fail in the real world) Strong programming skills in at least one of Go, Python, C++, or Rust, with willingness to work primarily in Go and Python on our codebase Comfortable with Git and a basic Linux command line Interest in puzzle-style debugging (for example: why did this workload restart?) without needing every answer on day one Preferred skill and experience Coursework or projects touching operating systems, networking, concurrency, or distributed systems at a high level Exposure to Docker or containers, or hands-on use of a cloud provider free tier or class account High-lev