Atita Arora

As a technically astute and business-minded Solutions Architect, I am deeply committed to partnering with our most strategic and high-impact platform customers to drive innovation and maximize the value of their solutions built on Qdrant's platform. With a focus on application ideation, development, delivery, and scalability, I leverage my expertise in LLM, data frameworks, and vector databases to guide customers through the entire lifecycle of their projects. Serving as a critical liaison between customers and internal teams, including Engineering, Partnerships, Research, and Product, I ensure that customer feedback is accurately collected and delivered to inform product enhancements. In this role, I thrive on deeply embedding with customers, providing proactive guidance to accelerate time to value, and experimenting with novel solutions to address their unique challenges. By forging and managing relationships with customer leadership and stakeholders, I drive successful deployments and scale for their applications. Additionally, I contribute to open-source initiatives, share knowledge, and scale the Solutions Architect function through codifying best practices and publishing educational resources. Leveraging my expertise in programming and the latest embedding models, I play a pivotal role in validating, synthesizing, and delivering high-quality feedback to drive continuous improvement across our products and research initiatives.

Search Relevance Consultant and Engineer with a solid foundation in software development and business strategy. Proven track record of successfully planning, implementing, and enhancing search functionalities for clients internationally. Skilled in building search applications for various domains including e-commerce, enterprise, and semantic search. Proficient in Natural Language Processing (NLP) and Semantic Web technologies, with a keen ability to leverage these tools to optimize search performance. Experienced in coaching teams during the introduction of information retrieval technologies and implementing recommender systems. Worked on Apache Solr, Lucene, Apache OpenNLP, OpenSearch, Elasticsearch, Vespa, SAP Hybris, .NET, Java and Python. Demonstrated ability to deliver innovative search solutions that drive business value and improve user experiences. Actively contribute to open-source projects on GitHub, notably as a contributor to [quepid](https://github.com/o19s/quepid) for experimentation on client information retrieval systems. Led vector search implementations in [chorus](https://github.com/o19s/chorus) and [chorus-opensearch-edition](https://github.com/o19s/chorus-opensearch-edition), showcased and presented at prestigious events including Berlin Buzzwords and ApacheCon 2023 Novascotia. Passionate about delivering innovative search solutions that drive business value and elevate user experiences.

Successfully delivered - Application migration to the AWS , architected Solr cloud with Kafka streaming in AWS and leverage cloud computation to speed up the index/ update pipelines, build/manage a microservices architecture along with addressing shortcomings in the product update cycles, long response times, heavy index footprint, and advance features like - spell-correction, auto-suggester, trending search terms on the shop portal and implementing the product recommendations using Learning to Rank and NLP in Solr.

Also led cross-functional teams for successful project execution while maintaining strong collaboration among team members.

Enhanced search capabilities for Germany's premier price comparison portal by spearheading the implementation of search functionality. Pioneered the setup of a new Solr Cloud infrastructure, integrating advanced NLP features to leverage insights from user search logs and keywords. Orchestrated the development and deployment of key features including spell correction, autosuggestion, and recommendation systems for both the Idealo Portal and mobile app. Drove the analysis and optimization of AB tests across various suggestion strategies, while also contributing to the creation of custom NLP models using cutting-edge unsupervised learning techniques such as Word2Vec.