Search Engineer

** Description*
* Leidos is seeking a Search Engineer to support, enhance, and modernize our enterprise search platform for a Federal customer. This role is responsible for both software development and operations & maintenance of search applications and indexing pipelines built on Apache Solr, Flume, Spark, Linux, Microsoft SQL Server, and AWS Open Search.

The engineer will ensure day-to-day reliability of indexing and retrieval services by addressing indexing failures, data issues, search syntax and relevance problems, performance degradation, vulnerability remediation, patching, and recurring maintenance activities. This role also supports bulk indexing operations, synonym refreshes, name normalization, data purges, and SLA restoration for search and retrieval services.

In addition to supporting the existing environment, this role will help evolve the platform toward modern search capabilities using AWS Open Search, semantic search, vector embedding, hybrid retrieval, and Retrieval-Augmented Generation (RAG). The ideal candidate combines strong hands-on troubleshooting and operational ownership with practical experience in search engineering, data pipelines, and cloud-based modernization.

** Key Responsibilities*
* + Maintain, support, and enhance enterprise search applications and indexing pipelines running on Solr, Spark, Flume, AWS Open Search, and Linux-based infrastructure.

+ Perform operations and maintenance activities including patching, vulnerability management, system administration, monitoring, configuration management, and routine platform support.

+ Troubleshoot and resolve indexing failures, data issues, query syntax problems, relevance issues, and search performance degradation.

+ Monitor indexing jobs and platform health to ensure indexing SLAs and search/retrieval SLAs are consistently met.

+ Fine-tune search configurations, analyzers, synonyms, ranking logic, and index structures to optimize search relevance, indexing throughput, and retrieval performance.

+ Perform scheduled maintenance activities including weekly, monthly, and biannual data purges, index cleanup, retention-related tasks, and storage optimization.

+ Support quarterly bulk indexing operations, including large-scale reloads, synonym refreshes, name normalization, and post-load validation.

+ Work with source data stored in Microsoft SQL Server to investigate ingestion issues, validate upstream data quality, analyze indexing results, and review operational or search-related metrics captured after indexing.

+ Use SQL to query source and operational data, investigate discrepancies, support troubleshooting, and validate indexing outcomes and SLA-related metrics.

+ Use Azure Log Analytics and related monitoring tools to analyze logs, investigate failures, identify operational trends, and support root cause analysis for indexing, search, and data-processing issues.

+ Maintain awareness of Java-based source-to-target data comparison and validation tools, review their findings regularly, and address data quality, synchronization, and accuracy issues between source systems and indexed search platforms.

+ Investigate and resolve data ingestion, transformation, indexing, and retrieval issues across upstream and downstream systems.

+ Build and improve automation, scripts, and support tooling that increases reliability, reduce operational overhead, and improve observability.

+ Support modernization of legacy search capabilities toward AWS Open Search, semantic search, vector search, hybrid retrieval, and RAG-enabled solutions.

+ Document procedures, runbooks, support processes, recurring maintenance activities, and operational findings, and collaborate with cross-functional teams to improve search quality and system stability.

** Required Qualifications*
* + Bachelor's degree in Computer Science, Engineering, Information Systems, or related field, or equivalent practical experience.

+ 5+ years of experience in software engineering, enterprise search, search platform support, information retrieval, or large-scale data systems.

+ Hands-on experience supporting and enhancing enterprise search platforms such as Apache Solr, Open Search,…