Overview
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.
Good to Have:
● Knowledge of recommendation systems and personalized ranking models.
● Familiarity with analytics-driven decision making (e.g., search dashboards, clickstream analysis). Success Metrics
● Improved Search Relevance Score (Click-Through Rate, conversion, engagement).
● Reduced Search Latency and improved scalability.
● Increased scientist satisfaction and time-to-product efficiency.
● Team health: retention, growth, and delivery predictability. Our benefits
● Working for a mission-driven business with a meaningful challenge with a positive impact on the scientific community
● A clear growth perspective
● A learning and development budget to enable your ambitions to grow professionally in your field
● A professional and dynamic team with a global vision and mindset ● An exciting, international working environment - we have more than 40 nationalities!
● We’ve got your health benefits (medical, dental, and vision)
● Hybrid Work with 3 days work from office in our HSR Layout, Bangalore office
● Staying healthy and fit is essential - we cover a part of your gym membership!
● Holidays and flexible PTO
● Paid family leave
● A budget to improve your home office environment