Senior Backend Search Engineer - Remote / Telecommute

Backend Senior Search Engineer

The Backend Senior Search Engineer will be responsible for optimizing search relevance, enhancing search engine performance, and implementing advanced AI/ML-powered search capabilities for eCommerce platforms. The role involves collaborating with cross-functional teams to improve search functionality, scalability, and user experience while maintaining high standards of engineering excellence.
Requirement/Must Have:

8+ years of hands-on experience in search relevance, search query optimization, and software engineering for eCommerce platforms.
Proven experience with Elasticsearch or other Lucene-based search engines such as Solr or OpenSearch.
Experience with lexical search algorithms such as BM25 and semantic search technologies.
Strong understanding of search relevance tuning, ranking, tokenization, stemming, and query parsing.
Experience building or integrating RAG-based architectures for LLM-assisted search solutions.
Experience with MLOps practices and tools.
Strong Python programming experience.
Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
Ability to collaborate effectively with cross-functional and global teams.
Strong analytical, problem-solving, and customer-focused mindset.
Excellent verbal and written communication skills.
Responsibilities:

Analyze and enhance search relevance algorithms to improve search accuracy and user experience.
Implement and manage search query optimization strategies aligned with user behavior and business objectives.
Oversee search engine configuration, tuning, and performance optimization.
Develop and implement AI and machine learning-based search functionalities including personalized and predictive search.
Collaborate with product owners, data scientists, and software engineers to implement search-related enhancements.
Monitor search performance metrics and user feedback to identify optimization opportunities.
Maintain documentation for search algorithms, tuning strategies, and system configurations.
Mentor and guide engineering teams while promoting innovation and engineering best practices.
Provide technical solutions aligned with business requirements.
Should Have:

Experience with Java, Kotlin, Spring, and Spring Boot.
Experience with Microservices, CI/CD, Event-Oriented Architectures, and Distributed Systems.
Experience with cloud platforms such as Google Cloud Platform, Microsoft Azure, or Amazon Web Services.
Familiarity with DevOps principles, Agile/Scrum methodologies, and product development lifecycle processes.
Experience leading product-oriented engineering development teams.
Familiarity with modern web APIs and full-stack frameworks.
Experience with Java, Google Analytics, BigQuery, Cassandra, Docker, Kubernetes, Kafka, and in-memory caching technologies.
Familiarity with data analysis and manipulation libraries such as Pandas, NumPy, and Spark.
Skills:

Search relevance optimization.
Search query optimization.
AI and machine learning integration.
Elasticsearch, Solr, and OpenSearch.
Python programming.
TensorFlow, PyTorch, and Scikit-learn.
SQL and NoSQL databases.
Microservices and distributed systems.
Cloud computing platforms.
CI/CD and DevOps practices.
Qualification And Education:

Bachelor’s degree in Computer Science, Engineering, Data Science, or a related quantitative field.