AI Product Manager (Remote — Worldwide)

As an AI Product Manager at Pinecone, you will define the future of high-performance retrieval infrastructure for the world’s most sophisticated GenAI applications. You will be responsible for scaling our managed vector database to handle trillions of embeddings while maintaining the industry's lowest latency and highest recall. By bridging the gap between cutting-edge research in Approximate Nearest Neighbor (ANN) search and enterprise-grade reliability, you will directly influence how developers build RAG setups and agentic workflows at scale.

- Lead the product lifecycle for Pinecone’s core vector search engine, prioritizing features that improve search relevance and indexing speed. - Partner with Engineering and Applied Science teams to implement advanced retrieval techniques like hybrid search, reranking, and dynamic metadata filtering. - Translate customer feedback from enterprise developers and AI startups into actionable product requirements and technical specifications. - Define and track key performance indicators (KPIs) related to developer onboarding, API reliability, and monthly active users. - Drive the pricing and packaging strategy for new serverless and pod-based storage tiers. - Evangelize Pinecone’s product vision at industry conferences and within the AI developer community through technical content and documentation. - Conduct competitive analysis of the vector database landscape to ensure Pinecone remains the industry gold standard.

- 4+ years of Product Management experience at a high-growth SaaS or infrastructure company. - Deep technical understanding of vector embeddings, transformer models, and the RAG (Retrieval-Augmented Generation) stack. - Proven track record of launching developer-centric products, APIs, or data infrastructure tools. - Strong analytical background with the ability to interpret performance benchmarks (latency, throughput, QPS) and cost-per-query metrics. - Experience working with distributed systems, Kubernetes, or cloud-native database architectures. - Outstanding communication skills with the ability to translate complex technical trade-offs into clear product roadmaps. - Self-starter mindset capable of thriving in a fully remote, globally distributed environment.

Equity, benefits, remote.