Staff Backend Engineer, Search
New
J
JobgetherAI Productivity Platform
USFull-TimeStaff
Salary$250,000–$300,000 USD
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Job Details
- Experience
- 7+ years
- Required Skills
- ElasticSearchTypeScriptPostgresDistributed Systems
Requirements
- Bachelor’s degree in Computer Science or a related technical field.
- 7+ years of professional experience as a search engineer or in a closely related backend engineering role.
- Strong hands-on production experience with OpenSearch or Elasticsearch; experience with Solr may also be considered.
- Proven experience designing and operating high-scale, real-time data ingestion and search-serving systems.
- Strong understanding of query parsing, indexing, relevance tuning, search optimization, and information retrieval concepts.
- Demonstrated experience measuring, evaluating, and improving search quality using data-driven approaches.
- Experience designing search architectures that maintain strong performance and reliability under heavy workloads.
- Strong software engineering and problem-solving abilities, with the capacity to troubleshoot complex distributed search systems.
- Experience collaborating effectively with backend engineers, AI/ML specialists, product managers, and other cross-functional stakeholders.
- Familiarity with search ranking, relevance algorithms, and information retrieval is highly desirable.
- Hands-on experience with vector embeddings and semantic search implementations is preferred.
- Experience applying machine learning or natural language processing techniques to improve search relevance is a plus.
- Experience with TypeScript in backend systems is desirable.
Responsibilities
- Design, implement, and evolve robust backend search solutions capable of scaling with a rapidly growing user base.
- Architect and optimize search infrastructure built on technologies such as OpenSearch, Elasticsearch, and Postgres.
- Improve search relevance, accuracy, latency, and overall result quality to help users quickly find the information they need.
- Build and optimize real-time indexing and ingestion pipelines so search results remain current and reliable.
- Develop measurement and evaluation frameworks that provide actionable insight into search quality and guide continuous improvement.
- Build and enhance vector search capabilities, including semantic search and embedding-based experiences.
- Optimize query parsing, indexing strategies, relevance tuning, and search-serving performance.
- Collaborate with AI, backend engineering, and product teams to integrate search capabilities.
- Investigate and resolve complex search-related production issues.
- Provide technical leadership on search architecture, engineering decisions, and scalable solutions.
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