Senior/Staff Software Engineer, Search & Retrieval Infrastructure

Pinecone is the knowledge infrastructure for AI at scale. Its leading vector database and knowledge engine, Pinecone Nexus, power accurate, performant AI applications for more than 9,000 customers and 800,000 developers worldwide. Pinecone's mission is to make AI knowledgeable. Pinecone is based in New York and raised $138M in funding from Andreessen Horowitz, ICONIQ, Menlo Ventures, and Wing Venture Capital. We are hiring a senior/staff software engineer to help design and build core components of our next-generation knowledge retrieval system built for the AI era – search and retrieval infrastructure that powers high-quality, scalable, and enterprise-grade agentic systems. You’ll build the framework that allows our customers to connect knowledge–synthesized from structured and unstructured data–to modern LLM-powered applications, leveraging the world’s best-in-class vector DB supporting semantic search and hybrid retrieval. This role is ideal for someone who loves backend system architecture, distributed systems, and applied AI infrastructure. It is a high impact role with significant ownership across architecture, performance, and system reliability.

Responsibilities

Design and build scalable platform components leveraging advanced retrieval via query planning, semantic and hybrid search, metadata-aware search, and LLM generation; Design and build optimized indexing pipelines for structured and unstructured data; Build backend services for semantic and hybrid retrieval, knowledge graph construction, and retrieval orchestration; Improve retrieval quality through evaluation and observability frameworks; Design APIs for internal and external user and agentic consumers; Optimize latency, throughput and cost across large-scale inference and retrieval workloads; Drive technical direction for reliability and security

Requirements

Deep passion for turning data into knowledge; Proven track record (typically 6+ years) of shipping production-grade backends for large-scale systems; Comfortable building high-throughput indexing pipelines that handle unstructured data and structured schemas; Direct experience or deep theoretical knowledge in semantic search, vector databases, hybrid retrieval strategies, or traditional search engines like Elastic or OpenSearch; Understanding of Retrieval-Augmented Generation (RAG) patterns, from embedding pipelines and hybrid search techniques to query planning and metadata filtering; Expert in at least one major language like Go, Rust, C++, Java, or Python; Familiarity and experience with Kubernetes, cloud-native architectures, observability frameworks, and infrastructure-as-code tools like Terraform or Pulumi; Ability to design clean, intuitive APIs for human developers and autonomous agents; Comfortable in a high-growth environment, preferring to own a problem over executing a ticket

Nice to have

Experience building multi-tenant SaaS platforms; Experience with retrieval evaluation frameworks; Experience with query planning or agentic reasoning loops

Benefits

Comprehensive health coverage including medical, dental, vision, and mental health resources; 401(k) Plan; Equity award; Flexible time off; Paid parental leave; Annual Company Retreat; WFH Equipment Stipend