Ll Oefentherapie
Principal Software Engineer, Storage - AI Infrastructure Innovation
Ll Oefentherapie, Boise, Idaho, United States, 83708
OCI (Oracle Cloud) AI Infrastructure Innovation team is inventing the next generation of storage technologies. You will lead architecture and hands‑on development across key layers: distributed processing, transactions, consensus, and storage engines. If you thrive at the intersection of large‑scale distributed systems, database internals, and cloud platforms, this role offers the opportunity to advance the state of the art.
Responsibilities
Lead end‑to‑end architecture, system design, and implementation for distributed storage platforms.
Innovate on query processing, transaction, and IO performance, and work across different components - query planning/optimization, distributed execution engine, index and storage engine.
Develop production‑grade, high‑performance software features with rigorous durability, correctness, observability, and security.
Define performance goals and success metrics; design benchmarks and conduct large‑scale experiments to validate throughput and latency.
Define consistency, replication, and recovery strategies.
Collaborate across storage, networking, compute, and control‑plane teams to deliver cohesive end‑to‑end solutions on OCI.
Mentor engineers, provide technical leadership and reviews, and influence multi‑year roadmap and technical standards.
Qualifications Required
Deep expertise in distributed systems with hands‑on delivery of large‑scale, fault‑tolerant, strongly consistent services.
Experience building distributed execution engines.
Proven ability to design for global scale: sharding/partitioning, placement policies, rebalancing, and multi‑region replication.
Strong software engineering background with performance profiling, correctness testing, and rigorous code quality.
Cloud architecture experience on a major public cloud, including observability, orchestration, and incident response.
BS/MS in Computer Science, Electrical/Computer Engineering, or equivalent practical experience; proven technical leadership and mentoring.
Preferred
Familiarity with high‑performance IO paths; understanding of cross‑region networking and latency trade‑offs.
Strong foundation in consensus and transactions.
Expertise with observability at scale: tracing, metrics, logs, eBPF/perf, chaos/failure testing, and SLO‑driven operations.
Knowledge of AI/HPC workload patterns and their implications for storage, query processing, and consistency models.
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Responsibilities
Lead end‑to‑end architecture, system design, and implementation for distributed storage platforms.
Innovate on query processing, transaction, and IO performance, and work across different components - query planning/optimization, distributed execution engine, index and storage engine.
Develop production‑grade, high‑performance software features with rigorous durability, correctness, observability, and security.
Define performance goals and success metrics; design benchmarks and conduct large‑scale experiments to validate throughput and latency.
Define consistency, replication, and recovery strategies.
Collaborate across storage, networking, compute, and control‑plane teams to deliver cohesive end‑to‑end solutions on OCI.
Mentor engineers, provide technical leadership and reviews, and influence multi‑year roadmap and technical standards.
Qualifications Required
Deep expertise in distributed systems with hands‑on delivery of large‑scale, fault‑tolerant, strongly consistent services.
Experience building distributed execution engines.
Proven ability to design for global scale: sharding/partitioning, placement policies, rebalancing, and multi‑region replication.
Strong software engineering background with performance profiling, correctness testing, and rigorous code quality.
Cloud architecture experience on a major public cloud, including observability, orchestration, and incident response.
BS/MS in Computer Science, Electrical/Computer Engineering, or equivalent practical experience; proven technical leadership and mentoring.
Preferred
Familiarity with high‑performance IO paths; understanding of cross‑region networking and latency trade‑offs.
Strong foundation in consensus and transactions.
Expertise with observability at scale: tracing, metrics, logs, eBPF/perf, chaos/failure testing, and SLO‑driven operations.
Knowledge of AI/HPC workload patterns and their implications for storage, query processing, and consistency models.
#J-18808-Ljbffr