Senior Staff Site Reliability Engineer, Lead

As SRE (Uber tech Lead) UTL, you will play a key role in driving the reliability, performance, and resilience of our most critical services. You’ll lead the strategy and execution for observability, incident management, capacity planning, and continuous improvement of our global scale production systems. You will be accountable for the response to novel, rare, or unexpected events encountered during the operation of our most critical systems. This includes both spearheading timely investigations and resolutions, as well as proactively partnering with engineering to evolve our software system to enhance their robustness and adaptability.This unique role encompasses our commercialisation services along with our planet scale software delivery systems, both of which underpin our rapidly growing and evolving fleet of autonomous vehicles operating in multiple cities. The challenges of ensuring reliability at our scale and pace is unprecedented. If you are a hands-on SRE tech lead, with strong software engineering skills, who is passionate about solving first-of-their-kind problems with significant real-world planet scale impact, we'd like to meet you.

This is a hybrid role and reports to the Head of Site Reliability Engineering.

You will:

• Drive incident response processes, retrospectives, and continuous improvement to prevent recurring issues. Organize and participate in on call rotations for release oriented outages, along with disaster recovery planning and business continuity
• Harden software, develop playbooks, improve oncall metrics and post-mitigation workstreams, and improve robustness of the software system running our most critical release processes
• Lead the engineering analysis and response to novel, rare or unexpected events encountered during our development analysis cycle.
• Champion a culture of reliability engineering across the organization, including partnering with organization leads and others across the Onboard, Eval and Simulator organization to educate and improve large-scale software engineering best practices.
• Contribute to system software architecture to help improve its robustness and debuggability

You have:

• Master's degree or PhD in Computer Science, Engineering, or a related technical field
• 15+ years of experience working on large-scale production software systems, especially machine learned systems
• 15+ years on hands on coding experience with C++
• Experience organizing and running oncall rotations
• Excellent influence without authority skills
• Organizational awareness, extremely collaborative, strong communication, focus on value add to the company and to the team
• Deep expertise in architecting large scale distributred systems, observability tools, monitoring systems, and incident management practices
• Strong background in distributed systems, cloud infrastructure, and production operations at scale
• Proficiency with automation, infrastructure and modern DevOps/SRE tooling
• Track record of improving system reliability through data-driven approaches and systematic problem-solving

We prefer:

• 15+ years of experience leading hybrid hardware/software production systems
• Experience leading teams who work on modern deep ML / large scale models
• Track record of bringing about change in 1000+ person engineering organizations