# Staff Backend Engineer, Search

**Company:** [ClickUp](https://hotfix.jobs/companies/clickup)
**Location:** Remote
**Role:** Backend Engineering
**Salary:** $250k – $300k/yr
**Experience:** 7+ years
**Skills:** Opensearch, Elasticsearch, Vector Search, Semantic Search, TypeScript, Machine Learning, NLP, Query Parsing, Indexing, Relevance Tuning
**Posted:** 2026-06-08

> Staff-level search engineer responsible for designing, scaling, and optimizing ClickUp's search infrastructure using OpenSearch/ElasticSearch, including real-time indexing, vector search, and relevance tuning.

## Job Description

## Core Responsibilities
- Design and implement robust search solutions that scale with our rapidly growing user base
- Improve search relevance, accuracy, and speed to deliver the most relevant results to users at blazing fast speeds
- Improve real-time indexing pipelines to ensure search results remain up-to-date
- Create measurement frameworks to evaluate and improve search quality
- Build and enhance vector search capabilities to power next-generation search experiences
- Collaborate with AI, backend, and product teams to integrate search into new features
- Troubleshoot complex search-related issues at scale
- Mentor junior engineers and contribute to engineering best practices

## Technical Requirements
- Bachelor's degree in Computer Science or related field
- 7+ years of experience as a search engineer or in a directly related role
- Strong expertise in search technologies, particularly OpenSearch / ElasticSearch
- Experience measuring and optimizing search quality
- Experience with high-volume, distributed data processing systems
- Proven ability to optimize query parsing, indexing, and relevance tuning for search systems
- Strong analytical and problem-solving skills
- Excellent communication skills and ability to collaborate effectively across teams

## Preferred Qualifications
- Hands-on experience with vector embeddings and semantic search implementations
- Experience with TypeScript in backend systems
- Track record of architecting search solutions that maintain performance under heavy load
- Experience applying machine learning and NLP to enhance search relevance
- Knowledge of information retrieval concepts and search evaluation metrics

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