Location: Richmond, VA
Work Arrangement: Onsite
Engagement: Contract
Experience: 5+ years overall, including 3+ years of hands-on Apache Solr experience
Position Overview
We are seeking an experienced Apache Solr Search Engineer to design, develop, optimize, and support enterprise search solutions.
The ideal candidate will have strong hands-on experience with Apache Solr/SolrCloud, search architecture, indexing, query optimization, relevancy tuning, performance engineering, and enterprise application integration.
Experience working with Guidewire applications and implementing enterprise search solutions within Guidewire environments is highly preferred.
Primary Skills
- Apache Solr,
- SolrCloud,
- Apache Lucene,
- Search Architecture,
- Search Engine Implementation,
- Indexing & Index Optimization,
- Solr Schema Design,
- Managed Schemas
- Dynamic Fields
- Custom Analyzers
- Search Query Development
- Query Performance Optimization
- Search Relevancy Tuning
- Boosting
- Faceting
- Highlighting
- Tokenization
- Stemming
- Search Filters
- Query Parsers
- Solr Administration
- Solr Performance Tuning
- Sharding & Replication
- REST APIs
- Java / J2EE Integration
- Search Troubleshooting
Secondary Skills
- Guidewire,
- Elasticsearch,
- Search Analytics,
- Relevance Engineering,
- AWS / Azure / Google Cloud Platform
- Linux
- Shell Scripting
- Git
- CI/CD
- DevOps
- Search Security & Access Control
- Search Governance
- SolrCloud Migration
- Large-Scale Dataset Management
- Enterprise Application Integration
- Insurance / Financial Services domain experience
Key Responsibilities
- Design and implement scalable enterprise search solutions using Apache Solr.
- Configure and manage Solr collections, cores, schemas, and indexing pipelines.
- Develop and optimize complex search queries, filters, facets, boosting, and relevancy models.
- Implement full-text search, autocomplete, spell checking, synonym management, and ranking capabilities.
- Analyze and improve search performance, indexing efficiency, and query response times.
- Integrate Solr with Java-based and web applications using REST APIs.
- Support and troubleshoot Solr environments, including indexing, replication, and cluster-related issues.
- Support SolrCloud deployments, including sharding, replication, scalability, and high availability.
- Work with business analysts and application teams to translate search requirements into technical solutions.
- Provide recommendations regarding search architecture, scalability, performance, and best practices.
- Monitor and troubleshoot search infrastructure and production issues.
- Support search optimization initiatives involving large document collections.
Required Qualifications
- 5+ years of overall IT/software engineering experience.
- 3+ years of hands-on experience implementing and supporting Apache Solr.
- Strong knowledge of Apache Solr/SolrCloud and Lucene-based search concepts.
- Strong understanding of indexing, tokenization, stemming, analyzers, filters, and scoring.
- Experience configuring schemas, managed schemas, dynamic fields, and custom analyzers.
- Experience with relevancy tuning, boosting, faceting, highlighting, and query parsers.
- Experience with Solr administration, monitoring, troubleshooting, and performance tuning.
- Strong understanding of REST APIs and enterprise integration patterns.
- Experience integrating Solr with Java/J2EE applications.
- Familiarity with Linux environments and scripting.
- Experience with Git or similar version control systems.
Preferred Qualifications
- Experience with Guidewire applications and enterprise search implementations.
- Experience with Elasticsearch or other search platforms.
- Cloud experience with AWS, Azure, or Google Cloud Platform.
- Experience in insurance, financial services, or other large-scale enterprise environments.
- Experience with CI/CD and DevOps practices.
- Knowledge of search security, access control, and governance.
- Experience migrating or upgrading SolrCloud environments.
- Search analytics and relevance engineering experience.
- Experience working with datasets containing millions of documents.
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy, sexual orientation, and gender identity), national origin, age, disability, genetic information, protected veteran status, or any other characteristic protected by applicable federal, state, or local law.
We are committed to providing reasonable accommodations to qualified applicants with disabilities and for sincerely held religious beliefs, as required by applicable law. Applicants who require a reasonable accommodation during the hiring process may request assistance.
Employment may be contingent upon the successful completion of job-related pre-employment screening, which may include background and reference checks and, where permitted by applicable law and applicable to the position, drug testing. All such screening will be conducted in accordance with applicable federal, state, and local laws.
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