Senior Search Engineer: Scalable Solr/Elasticsearch

Acesoft Labs; United States; Remote; USD 120,000 - 160,000; Full time

Job summary

Acesoft Labs is seeking an experienced Search Engineer to design and implement robust search architectures using Solr and Elasticsearch. You will write complex queries, optimize indexing, and tailor analyzers and mappings to domain data.

You will also develop Spark-based indexing pipelines and monitor performance across large datasets. The role requires 4–5 years of hands-on production experience with Solr/Elasticsearch, strong knowledge of Lucene internals and BM25/TF-IDF, and a proven ability

Qualifications

• 4–5 years hands-on experience with Solr and/or Elasticsearch in production environments.
• Proven ability to write and optimize complex Solr queries (standard, dismax, edismax) and Elasticsearch DSL.
• Understanding of indexing principles, Lucene internals, and relevance scoring (BM25, TF-IDF).
• Proficiency with Spark for custom indexing workflows and large-scale data processing.
• Experience with document parsing/extraction for search indexing and integrating search into applications.

Responsibilities

• Design and implement scalable search architectures using Solr and Elasticsearch.
• Write, optimize, and maintain complex search queries and DSLs.
• Build and manage analyzers, tokenizers, filters, and index mappings.
• Develop and optimize indexing pipelines using Apache Spark.
• Monitor and tune search performance and relevance metrics.
• Evaluate search quality, latency, and index refresh times.
• Create query templates and APIs for enterprise integration.

Skills

Solr

Elasticsearch

Query optimization

BM25

TF-IDF

Lucene internals

Apache Spark

Indexing pipelines

Tools

JSON parsing

XML parsing

PDF parsing

Job description

Acesoft Labs is seeking an experienced Search Engineer to design and implement robust search architectures using Solr and Elasticsearch. You will write complex queries, optimize indexing, and tailor analyzers and mappings to domain data.

You will also develop Spark-based indexing pipelines and monitor performance across large datasets. The role requires 4–5 years of hands-on production experience with Solr/Elasticsearch, strong knowledge of Lucene internals and BM25/TF-IDF, and a proven ability