Staff Site Reliability Engineer, Production Engineering

Role Description

As a Site Reliability Engineer focused on company-wide reliability strategy, you will play a crucial role in advancing Dropbox’s stability, observability, incident response, and operational excellence as AI technologies reshape how software is built and operated. You will help define the reliability strategy for a new chapter of agentic development and AI-enabled software delivery, including preparing Dropbox for increases in pull request volume, service complexity, incident patterns, and demand for debugging and monitoring tools. You will partner across Engineering, Product, and leadership teams to raise the bar for reliability, guide long-term platform investments, and ensure Dropbox continues to deliver dependable experiences for millions of users.

Responsibilities

• Define and evolve Dropbox’s company-wide technical reliability strategy to support the changing engineering environment created by AI-assisted and agentic software development.
• Set multi-year reliability goals, standards, and roadmaps across observability, debugging, incident management, service health, and operational readiness.
• Lead cross-team initiatives that reduce reliability risk as software delivery velocity, pull request volume, service complexity, and incident volume increase.
• Partner with engineering leaders and platform teams to improve monitoring, alerting, debugging, SLOs, SLAs, and incident response systems at company scale.
• Identify emerging reliability risks introduced by AI-enabled development workflows and design scalable systems, processes, and guardrails to mitigate them.
• Provide technical leadership and mentorship to engineers across teams, raising engineering quality, reliability judgment, and operational excellence.
• Drive clear communication and alignment with senior stakeholders on reliability priorities, tradeoffs, risks, and execution progress.

Many teams at Dropbox run Services with on-call rotations, which entails being available for calls during both core and non-core business hours. If a team has an on-call rotation, all engineers on the team are expected to participate in the rotation as part of their employment. Applicants are encouraged to ask for more details of the rotations to which the applicant is applying.

Requirements

• 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.

Preferred Qualifications

• 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.

Compensation