高级/资深软件工程师，搜索与检索基础设施
Senior/Staff Software Engineer, Search & Retrieval Infrastructure
关于 Pinecone
Pinecone 是一家值得信赖的 AI 知识公司。其可信 AI 知识平台——包括数据库、Nexus 和 Marketplace 产品——为全球超过 10,000 家客户和 100 万开发者提供准确、快速且成本效益高的 AI 应用。Pinecone 的使命是让 AI 更加知识化。更多信息，请访问 pinecone.io http://pinecone.io。
关于团队和职位：
我们正在招聘一位高级/资深软件工程师，帮助设计和构建面向 AI 时代的下一代知识检索系统的核心组件——用于高质量、可扩展和企业级代理系统的搜索和检索基础设施。你将构建一个框架，使我们的客户能够将从结构化和非结构化数据中提炼出的知识连接到现代 LLM 驱动的应用程序，利用世界级的向量数据库支持语义搜索和混合检索。这个职位适合热爱后端系统架构、分布式系统和应用 AI 基础设施的人。这是一个影响深远的职位，涉及架构、性能和系统可靠性方面的重大责任。
职责：
- 利用查询规划、语义和混合搜索、元数据感知搜索以及 LLM 生成，设计并构建可扩展的平台组件
- 设计并构建针对结构化和非结构化数据的优化索引流水线
- 构建用于语义和混合检索、知识图谱构建以及检索编排的后端服务
- 通过评估和可观测性框架提升检索质量
- 设计面向内部和外部用户及代理消费者的 API
- 在大规模推理和检索工作负载中优化延迟、吞吐量和成本
- 推动可靠性和安全性方面的技术方向
你将带来的能力：
要在这个职位上取得成功，不需要满足所有条件，但你应该对如何将数据转化为知识充满热情。
系统专业知识
- 架构深度：你有在大型系统中交付生产级后端的经验证明（通常为 6 年以上）。你不仅仅是编写代码；你会为高吞吐量、低延迟和长期可维护性进行设计。
- 数据工程经验：你熟悉构建高吞吐量的索引流水线，能够处理非结构化数据的复杂世界和结构化模式的严格世界。
AI 与检索
查看英文原文
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.