Lucidworks fusion Engineer/Developer

Job Description

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 .