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We are seeking a Senior Staff Engineer (L6) to lead the technical strategy and evolution of Uber’s Core Infrastructure Platform. As a Senior Staff Engineer, you are the principal architect of an ecosystem that handles 1M+ concurrent trips and massive-scale ML workloads. You will own the technical roadmap for our Compute, Foundations, and Software Networking stack, driving the shift from Service Provider to Strategic Partner. We aren't looking for a maintainer; we're looking for a visionary who can drive Platform Engineering 2.0. You will solve the hard problems of extreme scale—driving fleet utilization from 26% to 40%+, scaling GPU pools for Generative AI, and ensuring Security by Design across a global multi-cloud footprint.
Job Responsibility
Architect Strategic Efficiency: Own the technical vision to drive fleet-wide CPU utilization and unit-cost optimization through ARM adoption (targeting XM+ cores) and silicon diversity
Scale AI & ML Infrastructure: Define the architecture for shared GPU pools and high-performance clusters to support 300x larger ranking models and Autonomous Vehicle data ingestion
Modernize the Data Plane: Drive the convergence of Uber’s networking stack toward industry standards (Kubernetes, Envoy, CNI) while enhancing SkyEdge for active-active multi-cloud resilience
Enforce Foundations & Reliability: Lead the 100% Done-Done initiative, ensuring every service follows standardized safe-deployment (Starship) and reaches 100% zero-trust authorization
Agentic Augmentation: Integrate AI-driven Minions and AIOps into the infrastructure to automate 80% of alerts and unlock thousands of years of developer productivity
Cross-Org Influence: Partner with Delivery, Rides, and AV teams to ensure the infrastructure isn't just a container, but a competitive advantage that accelerates their time-to-market
Mentor Staff+ Engineers: Act as a force multiplier by coaching the next generation of technical leaders and influencing company-wide engineering standards
Requirements
12+ years of software engineering experience, with a focus on massive-scale distributed systems or infrastructure
Proven Track Record at Scale: Experience managing infrastructure that supports millions of concurrent users or petabyte-scale data processing
Deep Systems Expertise: Mastery of Kubernetes internals, container runtimes, and the Linux kernel, with the ability to debug impossible performance bottlenecks
Cloud-Native Fluency: Deep experience with cloud-native networking (Envoy, CNI, Service Mesh) and multi-cloud (AWS/GCP) architecture
Coding Proficiency: Expert-level proficiency in Go, Java, or C++
Leadership: Demonstrated ability to lead 40+ person technical initiatives and influence VPs and GMs on infrastructure investment
Nice to have
Hardware/Silicon Strategy: Experience optimizing software for ARM architecture or specialized AI hardware (GPUs/TPUs)
Open Source Leadership: Significant contributions to Kubernetes, CNCF projects, or other major infrastructure open-source communities
AIOps & Automation: Experience building self-healing infrastructure or using LLMs/ML to automate infrastructure operations and incident response