Senior/Staff Software Engineer, Search & Retrieval Infrastructure Job at Pinecone (Tel Aviv)

Job Description

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.

Job Responsibility

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

Systems Expertise: Architectural Depth: You have a proven track record (typically 6+ years) of shipping production-grade backends for large-scale systems
Systems Expertise: 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
AI & Retrieval: 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
Technical: 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
Ownership & Impact: Ambiguity Navigator: You’re comfortable in a high-growth environment. You prefer owning a problem over executing a ticket

Nice to have

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)

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Senior/Staff Software Engineer, Search & Retrieval Infrastructure

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