Senior/Staff Software Engineer - AI Knowledge Retrieval
Job Description
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Pinecone is the knowledge infrastructure for AI at scale. Its leading vector database and knowledge engine, Pinecone Nexus, power accurate, performant AI applications for more than 9,000 customers and 800,000 developers worldwide. Pinecone's mission is to make AI knowledgeable.
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.
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Pinecone
View Company ProfilePinecone (operating at pinecone.io) is a premier vector database and knowledge infrastructure platform engineered to power high-performance, real-time retrieval-augmented generation (RAG), semantic search, and AI agent memory at global scale. Founded in 2019 by former AWS and Yahoo AI research director Edo Liberty and led by CEO Ash Ashutosh, San Francisco-headquartered Pinecone replaces complex, self-hosted open-source vector search clusters with a fully managed, serverless database architecture. Under the hood, Pinecone enables engineering teams to index, filter, and search multi-dimensional vector embeddings with ultra-low latency, high recall, and instant updates without managing underlying index maintenance or infrastructure overhead. Backed by $138M in total venture funding from Andreessen Horowitz, ICONIQ Growth, Menlo Ventures, and Wing Venture Capital, Pinecone serves thousands of enterprises and developers building context-aware generative AI applications and agentic intelligence workflows.
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