Description
We are looking for a Staff Platform Engineer to own the database and storage foundation of World Labs. This is a high-impact systems role at the intersection of databases, distributed systems, and AI infrastructure. You will define how core data systems are designed, scaled, and operated in an environment where workloads are evolving quickly and requirements are often ambiguous.
Your responsibilities will include owning the design and evolution of the transactional systems that power the platform, defining architecture for database and storage systems under high-throughput, low-latency workloads, making and driving decisions around data modeling, indexing, replication, and consistency, debugging and resolving complex production issues, establishing standards for reliability, observability, and operability across the platform, partnering with product and research teams to support evolving and often ambiguous requirements, driving improvements in performance, scalability, and cost across the system, mentoring engineers and raising the bar for system design and technical decision-making.
Key qualifications include 10+ years of experience building and operating production systems at scale, with ownership of critical infrastructure, strong experience designing and operating transactional systems and databases, deep understanding of data modeling, indexing, transactions, concurrency, and consistency tradeoffs, experience owning systems with strict reliability and performance requirements in production, strong experience debugging complex production issues and reasoning about failure modes, experience designing distributed systems or large-scale infrastructure where tradeoffs are non-trivial, proven ability to define architecture and drive technical decisions end-to-end, strong judgment in balancing performance, reliability, and cost, ability to operate effectively in ambiguous, fast-moving environments with high ownership.
Preferred qualifications include experience with database internals, storage systems, or query engines, experience building infrastructure for AI/ML systems or data platforms, experience in early-stage or high-growth environments.