Design and architect search & recommendations platform, work on Next Generation architecture in addition to supporting and maintaining current platforms including legacy systems
Focus on improving search relevance, ranking and recommendations, personalization architecture
Microservices development to support the many services within search and science teams.
Provide technical leadership within the team and build partnerships with cross-discipline team members
Write code and develop search & recommendation services, data ingestion indexing pipelines
Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive search, discovery, and recommendations.
Work closely with other architects, engineers, data analysts, data scientists and project managers in assessing project requirements, design, develop and support data ingestions, API services and Elasticsearch stack solution
Work with Data Scientists in integrating ML Ranking models, NLP and applying query understanding techniques in search
Proven work on large-scale search, discovery, typeahead (auto-suggest), personalization, and recommendation implementation and its related infrastructure
Able to influence on priorities working with various partners including engineers, project management office and leadership
Mentor junior team members, define architecture, code review, hands-on development and deliver the work in sprint cycle
Participate in design discussions and other team members for the design of new systems and re-engineering of components of existing systems
Wear Architect hat when required to bring new ideas to the table based on past experience, thought leadership and forward thinking
Take holistic approach to building solutions by thinking big picture and overall solution
Perform a/b tests, work with Data Analysts and Data Scientists in evaluating the impact of search / recommendation improvements
Work on moving away from legacy systems into next generation architecture
Take complete ownership from requirements, solution design, development, production launch and post launch production support. Participate in regular on-call rotations.

Experience and Education:

BS or MS in Computer Science (or related field) with 12-15 years of hands-on software development (preferably in Java), architecture and technical mentorship experience
10+ years of experience in search technologies such as Elasticsearch / Solr / Lucene. Ideal candidate should have knowledge and experience in search relevancy advance techniques & query understanding.
10+ years of experience in building microservices / Rest APIs and data ingestion workers
10+ years of experience in using databases such as SQL Server, Dynamo, Redis and other NoSQL DBs
Nice to have experience in doing Vector Search using embeddings generated by ML models, Generative AI and conversational search
Experience in building large scale multi-region, fault-tolerant and resilient system
Software engineering skills in system architecture & design, coding, OOP, test driven development
Experience with multi-node clustering, ETL, monitoring of systems and APIs.
Knowledge of hot/warm/cold data, ILM (Index LifeCycle policies), Data streams, Transforms, CCR and other infrastructure aspect of services and Elasticsearch
Strong experience in building microservices, REST principles and design patterns
In-depth knowledge of Java, Docker, RESTful web services, Spring, Distributed caching techniques, Kubernetes, Observability techniques, Kafka, Release processes, versioning, Akamai, B&D, CI/CD pipelines, caching strategies
Phenomenal communication and influencing skills.

Nice to have:

Knowledge of Traditional Chinese and Simplified Chinese language would be an added advantage
Machine learning background in using ML in search, Learning to Rank, NLP, Generative AI, LLM models
Experience in Vector search / semantic search using vector search engines.
Experience in building real time indexing pipelines, Scala, Spark and other Big Data technologies.

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