Drive performance and efficiency: Optimize indexing throughput, query latency, resource utilization, and infrastructure costs across large-scale distributed systems.
Solve complex engineering challenges: Tackle problems involving distributed indexing, storage architecture, query execution, data freshness, scalability, and system reliability.
Shape platform architecture and strategy: Contribute to technical direction and architectural decisions that enable the platform to evolve with Uber's growing business and AI needs.
Collaborate across teams/organizations: Partner with engineering and product teams to understand diverse search requirements and deliver reusable, high-impact platform capabilities.
Basic Qualifications
Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
8+ years of professional software engineering experience, including significant experience designing and building large-scale distributed systems.
Strong expertise in distributed systems architecture, concurrency, data structures, algorithms, and performance optimization.
Proficiency in one or more systems or backend programming languages, such as Java, Go, Rust or C++.
Proven track record of architecting and delivering complex, production-grade infrastructure systems with high availability and scalability requirements.
Demonstrated ability to lead technically ambiguous, cross-team initiatives from architecture and design through execution and production adoption.
Strong technical judgment, communication, and collaboration skills, with the ability to influence engineering direction across teams.
Preferred Qualifications
Hands-on experience with search technologies such as Elasticsearch/OpenSearch, Solr, Lucene, or large-scale proprietary search systems.
Deep expertise in search engines and information retrieval systems, including Apache Lucene, OpenSearch, Elasticsearch, or similar technologies.
Strong understanding of indexing architectures, inverted indexes, query execution, relevance ranking, and distributed search systems.
Experience with vector search algorithms, such as HNSW, IVF, or other large-scale similarity search techniques.
Familiarity with semantic search, hybrid retrieval, embedding-based retrieval, retrieval-augmented generation (RAG), and agentic AI architectures.
Experience designing storage and compute architectures for large-scale, data-intensive systems, including compute-storage disaggregation, tiered storage, or distributed indexing.
Proven ability to drive substantial improvements in infrastructure efficiency, query latency, indexing throughput, or system reliability.
Experience evaluating emerging technologies and translating research or industry advancements into practical, production-grade infrastructure.
Track record of technical leadership, mentoring senior engineers, and influencing architectural direction across multiple engineering teams.
For San Francisco, CA-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 per year.
For Sunnyvale, CA-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 per year.
For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits.
