Senior/staff Software Engineer, Search & Retrieval Infrastructure

Pinecone Pinecone · Data AI · United States · Remote · R&D

Senior/Staff Software Engineer to design and build core components of a next-generation knowledge retrieval system for AI applications. The role focuses on search and retrieval infrastructure powering agentic systems, connecting knowledge to LLM-powered applications, and supporting semantic and hybrid retrieval. Responsibilities include designing scalable platform components, indexing pipelines, backend services for retrieval and orchestration, and optimizing performance for inference and retrieval workloads.

What you'd actually do

  1. Design and build scalable platform components leveraging advanced retrieval via query planning, semantic and hybrid search, metadata-aware search, and LLM generation
  2. Design and build optimized indexing pipelines for structured and unstructured data
  3. Build backend services for semantic and hybrid retrieval, knowledge graph construction, and retrieval orchestration
  4. Improve retrieval quality through evaluation and observability frameworks
  5. Design APIs for internal and external user and agentic consumers

Skills

Required

  • backend system architecture
  • distributed systems
  • Go, Rust, C++, Java, or Python
  • Kubernetes
  • cloud-native architectures
  • observability frameworks
  • Terraform or Pulumi
  • semantic search
  • vector databases
  • hybrid retrieval strategies
  • RAG patterns
  • embedding pipelines
  • hybrid search techniques
  • query planning
  • metadata filtering

Nice to have

  • multi-tenant SaaS platforms
  • retrieval evaluation frameworks
  • query planning
  • agentic reasoning loops

What the JD emphasized

  • shipping production-grade backends for large-scale systems
  • high throughput, low latency
  • high-throughput indexing pipelines
  • semantic search
  • vector databases
  • hybrid retrieval strategies
  • Retrieval-Augmented Generation (RAG) patterns
  • embedding pipelines
  • hybrid search techniques
  • query planning
  • metadata filtering
  • retrieval evaluation frameworks

Other signals

  • vector database
  • semantic search
  • hybrid retrieval
  • agentic systems
  • LLM-powered applications
  • retrieval infrastructure