Jobs at Pinecone

Build and ship end-to-end AI applications across frontend, backend, APIs, data pipelines, retrieval systems, and LLM integrations. Develop reference applications and reusable components, experiment with RAG and agentic architectures, and improve AI application quality, latency, reliability, and cost. Collaborate with customers, partners, product, and engineering teams while translating real-world problems into production software and sharing technical best practices.

Build and own end-to-end product experiences across APIs, SDKs, and web interfaces, including billing, authentication, usage dashboards, and cost reporting. Integrate billing systems and vendor APIs, develop observable and auditable systems, and collaborate with finance, product, design, and engineering teams. The role requires API design, React development, cloud experience, automation, and AI-assisted coding practices.

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.