5-7 years of experience in systems technologies, particularly in database systems and storage engines.
Hands-on experience designing and delivering for production systems, especially in AI workloads.
Demonstrated leadership in developing mission-critical products or subsystems, influencing technical direction.
Deep knowledge of vector search technologies and experience with vector databases like FAISS or Milvus.
Proven skills in high-quality system design, modular architecture, and maintainability.
History of engaging with open-source projects or published research in related fields.
Responsibilities
Architect and develop frameworks for serverless computing focused on AI workloads.
Lead innovation in vector database storage design within a large-scale AI infrastructure.
Drive advancements in vector indexing and retrieval algorithms for high-performance search.
Define the technical roadmap for next-gen vector database technologies.
Analyze industry trends and customer requirements to design tailored technical solutions.
Build scalable and reliable vector storage systems for production environments.
Benefits
Flexible work arrangements to support work-life balance.
Opportunities for career growth and skill development.
Collaborative and innovative team environment.
Health and wellness programs to support employee well-being.
Access to cutting-edge technology and resources.
Full Job Description
Architecting and develop frameworks and engines for next-generation serverless computing tailored to AI workloads (LLM training/inference, agent execution, RL training, etc.).
Lead the design and innovation of vector database storage engines within a large-scale Data + AI infrastructure platform.
Drive breakthroughs in vector indexing, retrieval algorithms, and storage architectures, enabling low-latency, high-throughput vector search at scale.
Define and evolve the technical roadmap for next-generation vector database storage technologies.
Stay deeply engaged with industry trends, open-source ecosystems, and competitive landscapes; translate customer requirements and real-world workloads into differentiated technical solutions.
Architect and build high-performance, scalable, and reliable vector storage systems used in production environments.
About the ideal candidate:
Proven ability to explore, design, and plan innovative systems technologies, with strong technical judgment and architectural thinking.
Deep understanding of database systems, storage engines, and vector search technologies, with hands-on experience designing and shipping production systems.
Lead the development of mission-critical products or subsystems, with successful delivery and commercial deployment.
Strong record of high-quality system design and execution, including component abstraction, modular architecture, and long-term maintainability.
Experience operating at Staff / Principal / Architect level, influencing technical direction across teams or organizations.
Experience with vector databases (e.g., FAISS, Milvus, HNSW-based systems, or custom implementations).
Background in distributed systems, storage systems, or AI infrastructure.
Contributions to open-source projects or published systems research.
