Senior Software Engineer, Knowledge Engine

Build scalable search and retrieval infrastructure for Pinecone's vector database and knowledge engine, focusing on semantic/hybrid search, indexing pipelines, RAG patterns, and LLM-powered agentic systems. Requires 6+ years building large-scale, low-latency backend systems with strong distributed systems and AI retrieval expertise.

About the job

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

6+ years of shipping production-grade backends for large-scale systems with focus on high throughput, low latency, and long-term maintainability.
Experience building high-throughput indexing pipelines handling 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, embedding pipelines, hybrid search techniques, query planning, and metadata filtering.
Expertise in at least one major language: Go, Rust, C++, Java, or Python.
Familiarity with Kubernetes, cloud-native architectures, observability frameworks, and infrastructure-as-code tools like Terraform or Pulumi.
Ability to design clean, intuitive APIs for both human developers and autonomous agents.
Comfortable owning problems in a high-growth, ambiguous environment.