Software Engineer, Infrastructure - Analytics Platform

We’re looking for a hands-on experienced software engineer who can take ownership of a critical system and drive it from problem definition through production adoption. This person should be able to own a platform such as CacheHouse end to end: define its technical direction, design its data model and storage architecture, integrate it with several research dashboards and workflows, guide one or two engineers, and ensure the system works reliably for its users.

Responsibilities

Own critical systems across architecture, implementation, integrations, deployment, monitoring, adoption, and whatever else is required to make them useful; Design, build, and operate the ingestion, storage, retrieval, and query systems behind research analytics at OpenAI; Build platforms for analyzing both structured metrics and unstructured research data, including samples, traces, evaluation results, and model-behavior data; Reason below typical service abstractions about algorithms, data structures, concurrency, storage layout, distributed systems, query performance, and failure modes; Make architectural tradeoffs across ingestion-time processing, data models, storage formats, indexing, query execution, caching, and visualization performance; Work directly with researchers to understand what they are trying to learn, ask the right questions, and challenge a requested solution when a simpler or more effective approach exists; Recognize when several teams are solving the same problem and turn those patterns into shared infrastructure, APIs, platform components, or agent-driven workflows; Write code, investigate production issues, make realistic estimates, guide other engineers, and think through testing, rollout, observability, and rollback; Keep solutions as simple as the problem allows.

Requirements

Own a critical distributed system or research platform end to end and explain how you took it from an ambiguous problem to reliable production adoption; Have experience with high performing programming languages (Rust or C++), including performance profiling, concurrency, async execution, memory behavior, serialization, I/O, networking, and failure analysis; Bring deep expertise in at least one relevant area such as distributed databases, storage engines, analytics systems, telemetry, logging, search, ingestion, or query execution; Reason carefully about partitioning, replication, consistency, retries, backpressure, event lineage, duplicate or delayed data, overload, migrations, and failure isolation; Have experience with ClickHouse or similar OLAP, columnar, time-series, or high-throughput analytical systems; Bring strong computer science fundamentals and algorithmic reasoning; Use coding agents regularly and have opinions about how AI tools change software development, product interfaces, and engineering leverage; Enjoy working directly with researchers and other highly technical users; Have the judgment to focus on the largest practical bottleneck rather than expanding every project into a complete platform rewrite; Be a strong engineer first. Clear communication and business judgment are non-negotiable, but your credibility comes from building and operating systems that work.

Nice to have

Direct ClickHouse experience; Competitive-programming experience