Constructor is the only search and product discovery platform tailor-made for enterprise ecommerce where conversions matter. Constructor's AI-first solutions make it easier for shoppers to discover products they want to buy and for ecommerce teams to deliver highly personalized experiences that drive impressive results. Optimizing specifically for ecommerce metrics like revenue, conversion rate and profit, Constructor generates consistent $10M+ lifts for some of the biggest brands in ecommerce, such as Sephora, Petco, home24, Maxeda Brands, Birkenstock and The Very Group. Constructor is a U.S. based company that was founded in 2015 by Eli Finkelshteyn and Dan McCormick. For more, visit: constructor.io.

Our new AI Shopping Assistant product utilizes novel approaches in the field, such as Retrieval Augmented Generation (RAG) and LLM Agents, to create an innovative shopping experience. The environment is super fast-paced and rapidly evolving. The team consists of a mix of designers, full-stack engineers, and machine learning engineers who own and collaborate on multiple projects. As a member of this team, you will play a crucial role in defining our product strategy and prioritization. You will use world-class analytical, engineering, and machine learning techniques to evolve and scale our AI Shopping Assistant.

Challenges you will tackle

• Build and deploy robust ML systems for personalized shopping experiences with the AI Shopping Assistant.
• Design and deliver products utilizing novel GenAI-based approaches, such as RAG and LLM Agents, to satisfy customer needs and drive revenue growth in an efficient manner
• Develop approaches for the evaluation and optimization of LLM-based pipelines to ensure a solid foundation for improving business KPIs by validating hypotheses.
• Optimize open-source LLMs to achieve high-quality performance in a narrow domain, enabling the use of these models without relying on large proprietary ones.
• Participate in strategic planning, brainstorming & prioritization sessions to improve the product 
• Collaborate with technical and non-technical business partners to develop analytical dashboards that describe the impact of the product to stakeholders.