Software Engineer, Infrastructure - Analytics Platform
$266k - $445k • Remote • San Francisco • FullTime
Posted 6mo ago
Job Location
San Francisco
Tech Stack
Remote Work Policy
Fully remote
Employment Type
FullTime
Categories
AI Infrastructure Engineer
About the job
We are seeking a hands-on, experienced software engineer to take ownership of critical systems within our Platform Analytics team. This role involves driving systems from problem definition through production adoption, defining technical direction, designing data models and storage architectures, and integrating with research dashboards and workflows. You will work directly with researchers to understand their needs, translate recurring problems into reusable infrastructure, and guide other engineers. The ideal candidate will possess strong technical judgment, ownership, and execution skills, with the primary learning curve being OpenAI's specific stack and research problems.
Responsibilities
- Own critical systems across architecture, implementation, integrations, deployment, monitoring, and adoption.
- Design, build, and operate ingestion, storage, retrieval, and query systems for research analytics.
- Build platforms for analyzing structured metrics and unstructured research data.
- Reason about algorithms, data structures, concurrency, storage, distributed systems, query performance, and failure modes.
- Make architectural tradeoffs related to data processing, models, storage, indexing, query execution, caching, and visualization.
- Collaborate with researchers to understand their learning objectives and challenge proposed solutions.
- Identify and consolidate recurring problems into shared infrastructure, APIs, or platform components.
- Write code, investigate production issues, provide estimates, guide engineers, and manage testing and rollout.
- Maintain simplicity in solutions and introduce complexity only when necessary for correctness, scale, latency, or reliability.
Requirements
- Experience owning a critical distributed system or research platform end-to-end.
- Experience with high-performing programming languages like Rust or C++.
- Proficiency in performance profiling, concurrency, async execution, memory behavior, serialization, I/O, networking, and failure analysis.
- Deep expertise in areas such as distributed databases, storage engines, analytics systems, telemetry, logging, search, ingestion, or query execution.
- Ability to reason about partitioning, replication, consistency, retries, backpressure, event lineage, data duplication/delay, overload, migrations, and failure isolation.
- Experience with OLAP, columnar, time-series, or high-throughput analytical systems (e.g., ClickHouse).
- Strong computer science fundamentals and algorithmic reasoning.
- Experience using coding agents and understanding their impact on software development.
- Enjoy working with technical users, debugging ambiguous problems, and explaining tradeoffs.
- Judgment to focus on the largest practical bottleneck.
- Strong engineering skills, clear communication, and business judgment.