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We're looking for an Infrastructure Engineer to build developer tooling that enables developer velocity and reliability for the entire engineering organization. Our team owns the full end-to-end development lifecycle, from local development tools, CI/CD, dynamic testing environments, deployments, and releases. You’ll be working with the latest cloud-native technologies as you build an infrastructure platform that enables the engineering organization to deliver observability for some of the largest technology companies.
Job Responsibility:
Architect & Build: Design and maintain high-scale developer tooling and backend services that improve productivity and reliability across a distributed cloud environment
Infrastructure as Code (IaC): Treat infrastructure as a first-class citizen
You will define, deploy, and manage entire environments using declarative IaC (Terraform), ensuring our platform is reproducible and version-controlled
Drive Systemic Quality: Identify and eliminate systemic bottlenecks in the software development lifecycle (SDLC) through architectural changes or advanced tooling
Scale & Reliability: Ensure our infrastructure remains resilient under massive traffic loads while optimizing for performance, cost-efficiency, and near-real-time telemetry processing
Strategic Leadership & Mentorship: Define platform standards and reference architectures that span a 1–3 year horizon, balancing feature velocity with long-term technical debt
Act as the "glue" across teams, consulting on infrastructure best practices and up-leveling the organization through mentorship
Requirements:
8+ years of relevant experience
Strong experience in at least one backend language (e.g., Go, Java, Python, or Rust)
Strong proficiency in at least one backend language (e.g., Go, Java, Python, or Rust)
Deep Systems Expertise: You go beyond "using" the cloud
you understand how it works
Cloud-Native: A solid understanding of cloud-native concepts and experience working with cloud providers like AWS or GCP
You should be comfortable navigating Kubernetes and container-level logic
Operating Systems & Compute: Deep knowledge of Linux internals, process management, and resource isolation
Networking & Security: Understanding of the OSI model, service meshes, load balancing, and "zero-trust" security architectures
Distributed Systems: Experience building and debugging systems that deal with CAP theorem trade-offs, eventual consistency, and distributed tracing
Reliable Execution: A track record of completing assigned tasks/tickets reliably and estimating work effectively within a sprint
You take ownership of features from local development through to basic testing and delivery
Analytical Debugging & Quality: The ability to debug your own code efficiently using logs and tests, while proactively identifying edge cases (like nulls or limits) during the design phase
Collaborative Spirit: Strong communication skills to keep teammates informed, raise blockers early, and contribute meaningfully to code reviews and design discussions
Continuous Learning: A proactive approach to learning new tools, processes, and libraries
You are open to feedback and use incidents or code reviews as opportunities to up-level your skills
AI-Native Development: You embrace the future of engineering
Experience or interest in using AI coding assistants (like Cursor or Claude) to improve productivity and automate boilerplate tasks