Overview
About the role As the Engineering Manager – eCommerce Search Experience, you will lead a team of talented engineers responsible for building and optimizing intelligent product discovery platform. You’ll shape how scientists,lab managers find products by improving search relevance, ranking, personalization, and end-to-end search performance. This role is ideal for a technical leader passionate about large-scale search systems, AI/ML-driven ranking, and building exceptional customer experiences in eCommerce.
Key Responsibilities
● Leadership & Strategy ○ Lead and grow a team of backend, and FE engineers focused on Search, Ranking, and Product Discovery.
○ Collaborate with Product, Data Engineering, and UX teams to define the long-term search roadmap.
○ Drive architecture and design discussions for scalable and intelligent search systems.
○ Foster a culture of high performance, collaboration, and continuous improvement.
● Technical Delivery ○ Oversee end-to-end design, development, and optimization of search pipelines (indexing, query processing, ranking). ○ Own search KPIs — including relevance, latency, clickthrough rate, and conversion metrics.
○ Implement experimentation frameworks (A/B testing, offline evaluation) to measure search quality improvements.
○ Guide migration or scaling of Elasticsearch/OpenSearch infrastructure and ensure data freshness, accuracy, and resilience.
● Stakeholder Management
○ Collaborate cross-functionally with product managers, UX designers, and marketplace stakeholders.
○ Communicate technical trade-offs, project risks, and roadmap progress effectively to business leadership.
○ Partner with analytics teams to translate user behavior data into actionable search insights.
Must Have:
● 8-12 years of total engineering experience, including 3+ years in a people management and technical leadership role.
● Strong technical foundation in search, ranking, and retrieval systems (Elasticsearch, OpenSearch, or similar).
● Proven experience in eCommerce search or large-scale catalog discovery systems.
● Proven experience in tracking sprint health, predictability, and delivery.
● Hands-on experience with Python/Java and modern backend frameworks.
● Experience designing data pipelines for indexing, enrichment, and query understanding.
● Understanding of search relevance tuning, synonyms, embeddings, re-ranking, and personalization.
● Strong architectural skills — ability to design scalable, high-availability search systems.
● Excellent communication, mentoring, and stakeholder management skills.
● Exposure to LLMs or vector search (semantic/embedding search) for product discovery.
● Experience with GCP, AWS, Kubernetes, and CI/CD for production-grade deployments.