Senior Software Engineer / Researcher, AI-Native database systems

What you'll do

• Architect AI-native databases, storage engines, and low-latency distributed vector search systems.
• Develop LLM-augmented query processing, RAG infrastructure, and memory backends for AI agents.
• Advance learned indexes, self-optimizing databases, and AI-integrated transaction systems; contribute to research and open source.

What they ask for

• Bachelor’s, Master’s, or Ph.D. in Computer Science or a related field, with strong systems or AI research experience.
• 2+ years in core database systems, large-scale distributed infrastructure, or machine learning systems.
• Strong coding and system-level design skills in C++ / Rust / Go.
• Deep expertise in at least one stated area: database storage engines; vector retrieval and ANN indexing; AI or model-serving infrastructure; or semantic search, agent systems, or AI-native memory frameworks.

Nice to have

• Experience with Faiss, Milvus, DuckDB, ClickHouse, TiKV, or RocksDB; or publications at accredited conferences such as SIGMOD, VLDB, NeurIPS, MLSys, or ICDE.
• Familiarity with GCP, AWS, or Azure database and AI integration strategies; or contributions to RAG, memory-augmented models, or self-tuning database components.

Tools

C++, Rust, Go, Faiss, Milvus, DuckDB, ClickHouse, TiKV

AI focus

Build AI-native database systems for AI workloads, including embedding ingestion, multimodal retrieval, LLM-assisted query processing, RAG infrastructure, and AI-agent memory backends.