(Key skills : Java, Microservices, Elasticsearch / Solr)
Job Description :
Essential Functions and Responsibilities
- Design and architect search & recommendations platforms, including next-generation and legacy systems.
- Focus on improving search relevance, ranking, recommendations, and personalization.
- Develop microservices to support multiple services within search and science teams.
- Provide technical leadership, build cross-discipline partnerships, and deliver reliable solutions.
- Write code and develop search & recommendation services, data ingestion, and indexing pipelines.
- Collaborate with architects, engineers, data analysts, data scientists, and PMs to build Elasticsearch stack solutions.
- Integrate ML ranking models, NLP, and query-understanding into search workflows.
- Work on large-scale search, discovery, typeahead (auto-suggest), personalization, and recommendation systems.
- Influence priorities, mentor juniors, review code, and ensure sprint delivery.
- Drive re-engineering of systems and migration from legacy to next-gen architectures.
- Take end-to-end ownership of design, development, production launch, and support.
- Participate in design reviews and on-call rotations for production systems.
Education and Experience
8+ years of hands-on software development (preferably Java), architecture, and technical mentorship.8+ years in search technologies (Elasticsearch, Solr, Lucene) with focus on relevancy and query optimization.8+ years building microservices, REST APIs, and data ingestion workers.8+ years using databases like SQL Server, DynamoDB, Redis, and other NoSQL DBs.Experience in Vector Search, Generative AI, Conversational Search preferred.Expertise in system design, OOP, TDD, and distributed architecture.Familiar with ILM, data streams, transforms, CCR, and Elasticsearch infrastructure.Strong background in Spring, Docker, Kubernetes, Kafka, distributed caching, and CI / CD.Excellent communication, collaboration, and influencing skills.