Staff Software Engineer, Scalable AI-Driven Search

Uber; United States; On-site; USD 232,000 - 258,000; Full time

Benefits offered by this job

Bonus program

Equity

401(k)

Benefits

Job summary

Uber's Search Platform team is building the next generation of scalable, intelligent retrieval infrastructure to power critical business apps and AI workloads. Staff Software Engineer candidates will tackle distributed systems challenges at Uber scale, shaping indexing and retrieval across the ecosystem.

You'll design high-performance search systems, advance lexical/semantic/vector/hybrid search, and enable agentic AI features while optimizing throughput and latency, collaborating across teams

Qualifications

• 8+ years in professional software engineering for large-scale distributed systems.
• Strong knowledge of distributed systems architecture, concurrency, and performance.
• Proficiency in Java, Go, Rust or C++.
• Proven track record leading cross-team initiatives.

Responsibilities

• Design and develop scalable, low-latency distributed search systems.
• Advance lexical, semantic, vector, and hybrid search capabilities.
• Enable AI-native and agentic applications on the platform.
• Optimize indexing throughput and query latency.
• Tackle problems in indexing, storage, query execution, scalability.
• Contribute to platform architecture and strategic direction.
• Collaborate with engineering and product teams across Uber.

Skills

Distributed systems

Backend languages

Technical leadership

High availability

Education

Bachelor's degree in CS/Engineering

Tools

Elasticsearch/OpenSearch

Lucene

Vector search

Job description

Uber's Search Platform team is building the next generation of scalable, intelligent retrieval infrastructure to power critical business apps and AI workloads. Staff Software Engineer candidates will tackle distributed systems challenges at Uber scale, shaping indexing and retrieval across the ecosystem.

You'll design high-performance search systems, advance lexical/semantic/vector/hybrid search, and enable agentic AI features while optimizing throughput and latency, collaborating across teams