5 Solr Search Jobs

Role & responsibilities 4 to 12 Years Skills : Senior Java Lucidworks, Solr, with Good Communication This role requires deep technical knowledge of Lucidworks Fusion (including Solr, Spark, and AI/ML integration), along with strong hands-on skills in data ingestion, pipeline development, query tuning, and relevance engineering.Key Responsibilities:Design & Development:Build end-to-end intelligent search solutions using Lucidworks Fusion.Develop custom ingestion pipelines, index configurations, query pipelines, and business rules.Create meaningful user experiences through relevance tuning, signals-based learning, and ML integration.Data Engineering:Configure connectors to ingest structured and unstructured data from multiple sources (SQL, NoSQL, REST APIs, etc.).Transform and enrich data during ingestion using Fusions Index Pipelines and JavaScript/Python scripting.Relevance Engineering:Apply signal-based personalization techniques and AI models to enhance relevance.Optimize ranking models using Fusion’s Smart Answers, Predictive Merchandiser, or Learning to Rank (LTR).System Integration & Deployment:Integrate Fusion with enterprise applications, microservices, and analytics platforms.Manage Fusion environments, handle deployments, and monitor system performance.Collaboration:Work closely with product managers, UX designers, and data scientists to meet business goals.Participate in Agile ceremonies, provide estimates, and maintain technical documentation.Required Qualifications:Bachelor's or Master’s degree in Computer Science, Engineering, or a related field.3+ years of hands-on experience with Lucidworks Fusion, Apache Solr, or similar enterprise search platforms.Strong expertise in search relevancy tuning, query pipeline development, and signals-based search.Proficiency in Java, JavaScript, Python, or Scala.Experience with data pipeline tools, ETL, and RESTful API integration.Solid understanding of Solr schema design, faceting, filtering, and query optimization.Familiarity with containerization tools (Docker, Kubernetes) and CI/CD pipelines.Excellent problem-solving and communication skills.Preferred Qualifications:Experience with Lucidworks Smart Answers, App Studio, AI-powered search use cases, or predictive merchandising.Familiarity with Apache Spark, Kafka, or cloud platforms like AWS, GCP, or Azure.Understanding of machine learning models and their integration into search platforms.Exposure to headless CMS, e-commerce search, or knowledge management systems. Preferred candidate profile

Key Responsibilities: Design and implement robust, scalable search architectures using Solr and Elasticsearch. Write, optimize, and maintain complex search queries (including full-text, faceted, fuzzy, geospatial, and nested queries) using Solr Query Parser and Elasticsearch DSL. Work with business stakeholders to understand search requirements and translate them into performant and accurate queries. Build and manage custom analyzers, tokenizers, filters, and index mappings/schemas tailored to domain-specific search needs. Develop and optimize indexing pipelines using Apache Spark for processing large-scale structured and unstructured datasets. Perform query tuning and search relevance optimization based on precision, recall, and user engagement metrics. Create and maintain query templates and search APIs for integration with enterprise applications. Monitor, troubleshoot, and improve search performance and infrastructure reliability. Conduct evaluations and benchmarking of search quality, query latency, and index refresh times. Required Skills and Qualifications: 4 to 5 years of hands-on experience with Apache Solr and/or Elasticsearch in production environments. Proven ability to write and optimize complex Solr queries (standard, dismax, edismax parsers) and Elasticsearch Query DSL, including: Full-text search with analyzers Faceted and filtered search Boolean and range queries Aggregations and suggesters Nested and parent/ child queries Strong understanding of indexing principles, Lucene internals, and relevance scoring mechanisms (BM25, TF-IDF). Proficiency with Apache Spark for custom indexing workflows and large-scale data processing. Experience with document parsing and extraction (JSON, XML, PDFs, etc.) for search indexing. Experience integrating search into web applications or enterprise software platforms.

Role & responsibilities Design and develop robust, scalable, and high-performance search engine components using Java. Implement indexing and retrieval logic for structured and unstructured data. Integrate with tools like Apache Lucene, Solr, or Elasticsearch. Develop and maintain APIs for search functionalities. Optimize query performance and relevance using techniques like TF-IDF, BM25, or vector-based retrieval. Collaborate with product managers, data scientists, and DevOps to define system requirements and deployment pipelines. Ensure code quality with unit/integration tests, code reviews, and documentation.

Knowledge on Solr search, schema for various data elements and prior experience in customize/implementations. Design, develop and improve open-source search APIs and SDKs Good understanding on Solr: Stemming, NLP, Result Grouping, Nested Fields, Ranking algorithms. Good knowledge about B2B commerce application and commerce objectives. Location- Remote, Delhi NCR, Bangalore, Chennai, Pune, Kolkata, Ahmedabad, Mumbai, Hyderabad

Role : Apache Solr consultant Role Type: Permanent Job Location: Pan India (remote) Experience: 6+ Yrs JD below : Mandatory skills: Java, Apache Solr, Micro services, spring boot