Senior/Staff Software Engineer, Search & Retrieval Infrastructure

Pinecone

Senior Software Engineer designing and building core components of knowledge retrieval infrastructure for AI. Engaging with scalable, performance-driven architecture handling both structured and unstructured data.

Posted 7/1/2026full-timeRemote • 🇺🇸 United StatesSenior💰 $190,000 - $270,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and building scalable backend services and indexing pipelines for both structured and unstructured data, with a strong focus on semantic search and retrieval optimization. Proficient in leveraging modern infrastructure tools and ensuring reliability and security in high-throughput environments.

Highest-signal resume keywords

Semantic SearchIndexing PipelinesBackend DevelopmentCloud-Native ArchitecturesRetrieval-Augmented Generation

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

GoRustC++JavaPythonSemantic SearchHybrid RetrievalIndexing PipelinesQuery PlanningMetadata Filtering

Soft Skills

Comfortable in High-Growth Environment

Tools & Technologies

KubernetesElasticOpenSearchTerraformPulumiObservability Frameworks

Industry Keywords

Large-Scale SystemsProduction-Grade BackendsStructured DataUnstructured DataRetrieval Quality

Tech Stack

Tools & technologies

CloudGoJavaKubernetesPythonRustTerraform

About the role

Key responsibilities & impact

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

What you’ll need

Proven track record (typically 6+ years) of shipping production-grade backends for large-scale systems
Comfortable building high-throughput indexing pipelines that handle both the messy world of unstructured data and the rigid world of structured schemas.
Direct experience (or deep theoretical knowledge) in semantic search, vector databases, hybrid retrieval strategies, or with traditional search engines like Elastic or OpenSearch.
Understanding the nuances of Retrieval-Augmented Generation (RAG) patterns, from embedding pipelines and hybrid search techniques to how query planning and metadata filtering can make or break an LLM's performance.
Expert in at least one major language like Go, Rust, C++, Java, or Python.
Familiarity and experience with modern infrastructure tools, such as Kubernetes, cloud-native architectures, and observability frameworks, as well as infrastructure-as-code tools like Terraform or Pulumi.
Comfortable in a high-growth environment.

Benefits

Comp & perks

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