Senior Backend Engineer, Tooling

Crusoe Crusoe · Data AI · San Francisco, CA - US · Cloud Engineering

This role is for a Senior Backend Engineer focused on building and scaling internal platforms and tools for customer success, support, and engineering teams within an AI infrastructure company. The primary focus is on enabling operational excellence, faster debugging, improving operational velocity through automation, and enhancing observability across distributed systems. While the company operates in the AI infrastructure space, the role itself is centered on backend engineering for internal tooling, not direct AI/ML model development or research.

What you'd actually do

  1. Build tools that allow internal teams to quickly diagnose and resolve customer issues across distributed systems.
  2. Develop workflows and automation that reduce time-to-resolution and eliminate repetitive manual tasks.
  3. Work closely with Customer Success, Support, SRE, and Product teams to identify gaps and deliver impactful tooling solutions.
  4. Design systems that support rapid growth in customers, infrastructure, and internal users.
  5. Enhance logging, metrics, and tracing capabilities to provide actionable insights across the platform.

Skills

Required

  • Proven experience building internal tools or platforms that improve developer productivity, operational workflows, or customer support capabilities.
  • Strong understanding of the needs of Customer Success, Support, or Operations teams, with a passion for improving their efficiency and effectiveness.
  • 5+ years of software experience in backend development.
  • Experience designing and operating scalable, fault-tolerant systems with strong observability and debuggability.
  • Familiarity with cloud platforms and infrastructure tooling such as Kubernetes, Docker, Terraform, and CI/CD systems.
  • Demonstrated ability to work deeply with non-engineering stakeholders (Customer Success, Support, Operations) to translate needs into technical solutions.
  • A strong inclination toward eliminating manual processes through automation and building self-service capabilities.
  • Experience mentoring engineers and influencing technical direction across teams.
  • Ability to clearly articulate technical concepts and trade-offs to both technical and non-technical audiences.

What the JD emphasized

  • internal tools
  • internal tooling
  • customer success
  • support
  • engineering teams
  • debugging
  • distributed systems
  • observability
  • automation