Staff Site Reliability Engineer, Production Engineering

Dropbox Dropbox · Enterprise · Canada +2 · Cloud Platform (Sub Team)

Staff Site Reliability Engineer focused on company-wide reliability strategy, advancing Dropbox’s stability, observability, incident response, and operational excellence as AI technologies reshape software development. The role involves defining reliability strategy for agentic development and AI-enabled software delivery, preparing for increased complexity, and partnering across teams to raise reliability standards and guide platform investments.

What you'd actually do

  1. Define and evolve Dropbox’s company-wide technical reliability strategy to support the changing engineering environment created by AI-assisted and agentic software development.
  2. Set multi-year reliability goals, standards, and roadmaps across observability, debugging, incident management, service health, and operational readiness.
  3. Lead cross-team initiatives that reduce reliability risk as software delivery velocity, pull request volume, service complexity, and incident volume increase.
  4. Partner with engineering leaders and platform teams to improve monitoring, alerting, debugging, SLOs, SLAs, and incident response systems at company scale.
  5. Identify emerging reliability risks introduced by AI-enabled development workflows and design scalable systems, processes, and guardrails to mitigate them.

Skills

Required

  • BS degree in Computer Science or related technical field involving coding (e.g., physics or mathematics), or equivalent technical experience.
  • 12+ years of experience in software engineering, site reliability engineering, infrastructure engineering, or related technical roles.
  • Proven ability to define and deliver multi-year, multi-team reliability, infrastructure, or platform strategies with measurable business and customer impact.
  • Deep experience with distributed systems, production operations, observability, incident response, SLOs/SLAs, debugging, and reliability risk management.
  • Demonstrated ability to diagnose complex technical problems, debug production systems, automate operational workflows, and design resilient software components.
  • Experience influencing engineering roadmaps across multiple teams and making technical decisions that optimize for the broader engineering organization.
  • Strong communication and collaboration skills, with the ability to align cross-functional stakeholders through ambiguity and drive execution across teams.

Nice to have

  • Experience adapting reliability strategies, developer tooling, or operational processes for AI-assisted software development workflows.
  • Experience building or scaling observability, debugging, incident management, or developer productivity platforms for large engineering organizations.
  • Experience leading reliability improvements in environments with high deployment velocity, complex service dependencies, and large-scale production systems.
  • Track record of mentoring senior engineers, setting technical standards, and spreading reliability best practices through documentation, reviews, talks, or architecture guidance.
  • Familiarity with AI-enabled tooling, agentic development workflows, or operational risks introduced by rapid automation in the software development lifecycle.

What the JD emphasized

  • AI technologies reshape how software is built and operated
  • agentic development
  • AI-enabled software delivery
  • reliability strategy
  • agentic development workflows
  • AI-enabled development workflows