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Lead technical product marketing for a vector database platform: develop GTM and launch plans, craft technical positioning and messaging, gather customer and market insights, create enablement content, and collaborate with Product, Sales, DevRel, and Marketing to drive adoption.

Design and build scalable backend components and indexing pipelines for semantic and hybrid retrieval, build retrieval orchestration and knowledge-graph services, improve retrieval quality via evaluation and observability, design APIs, and optimize latency, throughput, cost, reliability, and security for large-scale AI inference and retrieval workloads.

As a Software Engineer on the Database Team at Pinecone, you'll design and build features for AI applications, enhance performance, and support distributed systems with a focus on learning and collaboration.

Design and build scalable search and retrieval infrastructure: indexing pipelines, backend services for semantic and hybrid retrieval, knowledge graph construction, retrieval orchestration, APIs, and observability to optimize latency, throughput, cost, reliability, and security for large-scale LLM-powered systems.

Lead design and delivery of end-to-end developer and agent experiences across API, SDK, CLI, and web. Pioneer agent interfaces and MCP protocols, build high-leverage platform tooling, and establish AI-assisted development and observability for production systems.

Lead the design and development of Pinecone's API and interfaces for AI agents, focusing on automation and observability while collaborating with cross-functional teams.