• Lead architecture and development of high-performance, cloud-native Entity Resolution APIs. • Design and implement batch and streaming data pipelines using tools like Kafka, SQS, and Spark to build and update the underlying search index. • Build and maintain low-latency search APIs powered by ElasticSearch or Vespa to support real-time entity linking. • Collaborate with data scientists to integrate and deploy ranking models to improve search result quality. • Own the end-to-end lifecycle of applications deployed on Kubernetes, from development and CI/CD to monitoring and scaling. • Conduct performance tuning and debugging of search systems under high throughput and low-latency requirements. • Develop tools and metrics to benchmark search quality and system performance. • Partner with cross-functional teams in data science, infrastructure, and product to deliver reliable, scalable solutions. • Lead design discussions and planning for backend services that incorporate model inference, SQL/NoSQL and Graph databases.