Backend Sr Search Engineer

ESSENTIAL JOB FUNCTIONS

• Search Relevance Optimization:
  Analyze and enhance search relevance algorithms to ensure accurate and relevant search results for users.
• Search Query Optimization:
  Implement and manage search query optimization strategies to optimize search results based on user behavior and business objectives.
• Search Engine Management:
  Oversee the configuration and performance of search engines, ensuring they meet the evolving needs of the eCommerce platform.
• AI/ML Integration:
  Leverage AI and machine learning technologies to develop and implement advanced search functionalities, including personalized search results and predictive search capabilities.
• Collaboration:
  
  Work closely with product owner, data scientists, and software engineers to define and implement search-related features and improvements.
• Performance Monitoring:
  Monitor search performance metrics and user feedback to identify areas for enhancement and implement data-driven solutions.
• Problem-Solving:
  Excellent analytical and problem-solving skills, with the ability to think critically and creatively.
• Communication:
  Strong verbal and written communication skills, with the ability to articulate complex technical concepts to non-technical stakeholders.
• Documentation:
  Maintain clear documentation of search algorithms, tuning strategies, and system configurations for internal teams.

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

• 8+ years of hands‑on experience in search relevance, Search Query Optimization, and software engineering for eCommerce websites
• Proven experience with at least one major search engine, preferably Elasticsearch (or any Lucene‑based engine such as Solr or Open Search)
• Experience in lexical search using algorithms like BM25 and Semantic Search
• Deep understanding of search relevance tuning, search query optimization, ranking, tokenization, stemming, and query parsing
• Experience building or integrating RAG‑based architectures for LLM‑assisted search use cases
• Experience with MLOps practices and tools
• Proven experience in Python and familiarity with ML frameworks such as Tensor Flow, PyTorch, or Scikit‑learn
• Recent experience in Java, Kotlin, Spring, and Spring Boot is a plus
• Mentor and guide engineers across the team, promoting a culture of engineering excellence and experimentation
• Ability to provide solutions based on business requirements
• Ability to collaborate with cross‑functional teams
• Ability to work with global teams and maintain a flexible work schedule
• Must have excellent problem‑solving skills and be customer‑centric

• Experience with Microservices, CI/CD, event‑oriented architectures, and distributed systems
• Experience with cloud environments (e.g., Google Cloud Platform, Azure, Amazon Web Services)
• Experience leading product‑oriented engineering development teams is a plus
• Familiarity with Dev Ops practices/principles, Agile/Scrum methodologies, CI/CD pipelines, and the product development lifecycle
• Strong background in SQL and No
  
  SQL databases
• Familiarity with modern web APIs and full‑stack frameworks is a plus
• Experience with Java, Google Analytics, Big Query, Cassandra, Docker, Kubernetes, Kafka, and in‑memory caching is a plus
• Familiarity with data manipulation and analysis libraries (e.g., Pandas, Num Py, Spark) is a plus