Jamie Turner

Jamie Turner is the co-founder and chief executive of Convex, a reactive application-development platform that handles database operations, synchronization, and background workflows. His work applies experience building Dropbox’s storage and synchronization infrastructure to a newer challenge: helping developers and AI coding agents create stateful applications without assembling elaborate backend systems.

Turner was head of engineering at Bump, the mobile application acquired by Google in 2013. At Dropbox, he became a principal engineer and contributed to Magic Pocket, the company’s in-house storage infrastructure, including work on a custom file system. He also helped redesign Dropbox’s synchronization engine before becoming a senior engineering director leading its Business Platform and Storage / Databases groups.

He founded Convex with fellow Dropbox engineers James Cowling and Sujay Jayakar. Their platform treats the backend as a coordinated programming environment, bringing databases, transactions, synchronization, and background processing closer to application code. Turner’s public software projects, including work on storage, locking, and Haskell network services, reflect his longstanding interest in databases, protocols, and functional programming.

Convex released version 1.0 in July 2023 and published its backend source code in March 2024, enabling local development and self-hosting. That release used the Functional Source License, with conversion to Apache 2.0 after two years. In 2025, Convex joined the Open Source Pledge to support maintainers financially. The company announced a $57 million Series B in August 2026.

• Reactive backend architecture. Convex extends React-style state management into the backend: queries track data dependencies, clients subscribe to changing results, and mutations propagate updates without custom polling or cache-invalidation systems.

• The software-defined database. Turner argues that application code can define database behavior, including authorization, validation, and transactional guarantees, keeping critical rules understandable within familiar programming abstractions.

• Stateful AI application workflows. AI products frequently combine transcription, summarization, embeddings, retrieval, and concurrent generation tasks. Turner’s AI Engineer World’s Fair appearance illustrated how reactive queries, native vector indexes, and Convex Components synchronize these processes with user interfaces as intermediate results arrive.

• Infrastructure designed for AI coding agents. Turner argues that agents build more effectively when application behavior is visible in code, dependencies remain locally understandable, and transactional boundaries reduce hidden race conditions. The objective is infrastructure that makes agent-generated software easier for humans to inspect and safer to operate.