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