We are seeking a Senior Engineer with deep expertise in Apache Solr to design, build, and optimize scalable search solutions. This role focuses on improving search performance, relevancy, and indexing pipelines in a cloud-based environment. You will own search relevance across both traditional keyword-based and modern semantic (vector-based) retrieval.

Req.#989600929

Responsibilities

Design, build, and maintain Solr-based search platforms
Optimize search relevancy, ranking, and query performance
Build and manage indexing pipelines for large datasets
Deploy and operate services in AWS
Collaborate with cross-functional teams on search and recommendation features
Explore and implement ML-driven enhancements for search
Define and implement hybrid search strategies combining keyword and vector-based retrieval
Build and operate vector search pipelines within Solr/Lucene
Measure and improve search relevance using evaluation metrics and experimentation
Maintain Solr in production (SolrCloud), including collections, sharding, replication, and scaling
Establish monitoring, SLOs, runbooks, and participate in incident response and root cause analysis

Requirements

Strong experience with Apache Solr and backend development (Java or similar)
Experience working with AWS
Solid understanding of search architecture, indexing, and performance optimization
Experience designing and tuning search relevance strategies
Hands-on experience with SolrCloud in production environments
Familiarity with vector search and modern retrieval techniques

Nice to have

Experience with machine learning in search or recommendation systems
Familiarity with Elasticsearch or OpenSearch
Experience with distributed systems and large-scale data processing
Exposure to embedding-based retrieval and approximate nearest neighbor (ANN) algorithms
Experience with re-ranking or learning-to-rank approaches

An artificial intelligence system is software that is developed with one or more techniques that can, for a given set of human-defined objectives, using algorithmic information processing, generate outputs such as content, predictions, recommendations, or decisions with varying levels of autonomy (“AI”). Tasks that humans have traditionally done by thinking and reasoning are increasingly being done by, or with the help of, AI to help create efficiencies. EPAM may use AI during the recruitment process, in connection with collecting or processing your personal data. Some (non-exhaustive) examples of tasks that EPAM may use AI for include conducting initial screening, creating transcripts of interviews, and assessing applications/CVs against defined job description criteria to make suggestions to the individuals evaluating your candidacy. Your personal data and the results of any processing are not shared with AI applications outside of EPAM infrastructure. While EPAM may use AI to help create efficiencies during the recruitment process, EPAM does not use AI to make hiring decisions, which is done by EPAM Talent Acquisition and management.

EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our clients, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.
Engineer the Future with a Career at EPAM

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