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Senior/Staff Software Engineer, Search & Retrieval Infrastructure

Pinecone

5mo ago

Senior/Staff Software Engineer, Database Team

Pinecone

New York City

5mo ago

Principal Software Engineer - Vector Search - Elasticsearch

Elastic

United States

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Senior/Staff Software Engineer, Search & Retrieval Infrastructure

Pinecone

Listed 5mo agoListing ends Dec 28, 2026

Compensation: $190k–$270k
Location: Not stated
Fully remote
Employment: Full-timeSenior
Category: R&DAI / ML

Role skills

vector database rag embeddings go rust python kubernetes terraform

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About the job

3 min read10 sections

About Pinecone

Pinecone is the trusted AI knowledge company. Its trusted AI knowledge platform—including its Database, Nexus, and Marketplace products—power accurate, fast, and cost-effective AI applications for more than 10,000 customers and 1M developers worldwide. Pinecone's mission is to make AI knowledgeable. For more information, visit pinecone.io http://pinecone.io.

About the Team and Role

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

What You’ll Bring to the Table

To thrive in this role, you don't need to check every single box, but you should be deeply passionate about how to turn data into knowledge.

Systems Expertise

Architectural Depth: You have a proven track record (typically 6+ years) of shipping production-grade backends for large-scale systems. You don’t just write code; you design for high throughput, low latency, and long-term maintainability.
Data Engineering Savvy: You’re comfortable building high-throughput indexing pipelines that handle both the messy world of unstructured data and the rigid world of structured schemas.

AI & Retrieval

Retrieval Intuition: You understand that "search" is more than just a keyword match. You have direct experience (or deep theoretical knowledge) in semantic search, vector databases, hybrid retrieval strategies, or with traditional search engines like Elastic or OpenSearch.
RAG & Orchestration: You understand 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.

Technical

Language Fluency: You are an expert in at least one major language like Go, Rust, C++, Java, or Python.
Infrastructure: 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.

Ownership & Impact

Product Thinking: You don't just build to spec; you build for the user. You can design clean, intuitive APIs that both human developers and autonomous agents will love.
Ambiguity Navigator: You’re comfortable in a high-growth environment. You prefer "owning a problem" over "executing a ticket."

Bonus Points

Experience building multi-tenant SaaS platforms.
Experience with retrieval evaluation frameworks—knowing how to actually measure "good" search results.
Experience with query planning or agentic reasoning loops (e.g., teaching a system how to break down a complex prompt into multiple specific steps).

Perks & 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

All qualified applicants will receive considerations for employment without regard to race, color, religion, sex, age, disability, marital status, familial status, sexual orientation, pregnancy, gender identity, gender expression, national origin, ancestry, citizenship status, veteran status, and any other legally protected status under federal, state, or local anti-discrimination laws.

Role signals

Benefits: Health insurance, Dental insurance, Vision insurance, Paid parental leave, Flexible PTO, Mental health support, Equipment stipend, Company retreats

About Pinecone

Pinecone is a fully managed vector database built for AI, offering instant searchability, automatic indexing, and fast queries at any scale. The company provide…Based on an AI summary from pinecone.io