Andrei Lopatenko

AI-driven platforms for national security and defense. Applied AI and Generative AI, agentic search and agentic AI tools, AI modeling, machine learning, data science, optimization, and operations research. AI-powered solutions for logistics, supply chain management and analysis, production, sustainment, modernization and MRO, and capacity simulation. Work delivered through both forward-deployed teams and core AI platform data science teams.

Led the development of scientific Generative AI and agentic models powering Neuron7’s agentic search, question answering, and problem resolution capabilities within the service resolution AI stack. Oversaw the creation of advanced document understanding, knowledge graph extraction, and deep technical document comprehension combining text and visual information, designed to optimize service resolution workflows. These innovations demonstrably improved operational metrics, including repair and maintenance times, part usage, and other key business outcomes. Defined and executed the vision and roadmap for agentic AI for the C-suite, aligning research, engineering, and product teams to deliver strategic outcomes. Successfully launched multiple AI agentic products, enabling enterprise teams to leverage AI solutions at scale and generating measurable business impact for customers. Established frameworks and processes for enterprise AI development, building core products and supporting customer-specific AI solutions. Partnered with customer success teams to drive adoption of AI tools, scaling deployments across multiple clients while ensuring direct improvements in their operational and business performance.

2025 Building Deep Research Systems, Maven Deep Research and Agentic Search, Data Phoenix ICDM MMSR ‘25, Workshop on Multimodal Search and Recommendations 2024 Gen AI from Boom to Realization : Generative AI Conference, Munich, Germany, July LLM Evaluation, AI Camp, May Generative AI in Search, Analytics Vidhya, May Future of AI in Search, Gen AI Roadmap for Search and recommendations (private strategic briefings, executive presentations) Gen AI for Leaders Bootcamp, Maven, Apr LLM Evaluation, Gen AI ROI (private strategic briefings, executive presentations) Generative AI and Applications, UK-USA Smart Cities Forum 24, Apr LLMs for Search, Recommendation, and Personalization, HomeDepo, Apr Evaluating LLMs and LLM Systems : Pragmatic Approach, Analytics Vidhya, Apr Evaluating LLMs for Production Systems : Methods and Practices, Data Phoenix, Feb Evaluation of LLMs and LLM applications, Zurich, Jan 2022 Apex, Cloud Transformation Panel, July 22, Aug DataOps Unleashed, Panel, Feb 2021 NLP in Search and Enterprise AI, Baidu research, Nov NLP summit, oct NLP Panel, OnCon, Jul NLP at Scale, SDSC, Jul NLP for business success and customer experience, Data Lake and Analytics, Jul NLP at Scale, MLCon Jul AI Platform panel, StateOfTheArt, Jun Home Depot's AI Insights, Deep Learning, May NLP At Scale, MLOps: Production and Engineering, Mar Driving Customer Experience and Business Revenues: Search, Recommendation Engines, Big Data and Analytics, Canada, Mar Interview, Develomentor podcast, Jan 2020 The AI & Automation Revolution; Panel, Dec How to build a successful career in NLP, Nov AI and Big Data Expo, AI in multi-billion search engines. Nov AI in multi-billion search engines. Building AI and Search teams, Keynote, Sep Robert Walters Roundtable: Hiring Coders During Covid, August A. Lopatenko, Aziz Nazha, “Predicting the Unpredictable: AI Practices for the Pandemic Landscape , A panel discussion at AI Champions, AI in multi-billion search engines, AI Festival,

Led a broad portfolio of AI science and engineering organizations spanning Search, Discovery, User Understanding, Growth AI, Recommendations, Personalization, Conversational AI and NLP, Marketing AI, Call Intelligence and Analytics, and Generative AI and LLM science. Led AI research and engineering teams responsible for building and operating large scale AI products and platforms serving hundreds of millions of users. Built multiple AI organizations from the ground up, growing teams from zero to dozens of scientists and engineers across Conversational AI, Search and Discovery science, Generative AI research, and applied AI platforms. Led the launch of major AI powered products and platforms, including natural language search, advanced multi objective ranking for search and discovery, Next Best Action decision platforms, GenAI powered search and personalization, a Call Center AI platform supporting multiple enterprise use cases, and large scale computer vision systems for image understanding. Built the conversational AI organization and launched a full conversational AI stack. Led the development and launch of a scalable Generative AI platform and infrastructure supporting customer facing and internal applications across search, discovery, and voice based conversational understanding. Defined platform architecture and aligned engineering, operations, product, and business stakeholders. Established the GenAI platform as shared infrastructure enabling multiple teams to build and deploy AI powered products. Directed AI research programs in multi objective ranking, NLP, document and speech understanding, Generative AI, large language models, multimodal models, search and recommender systems science, user modeling, and propensity modeling, including end to end foundation model development and training pipelines for search, discovery, recommendations, and conversational systems.

Led global, multi-national, multi-role search science and engineering teams across San Jose, New York, Berlin, and Shanghai, responsible for all science aspects of Search and Discovery, including relevance, query understanding, ranking, navigational panels, autosuggest, search assistance, and customer engagement. Directed the global Search Science organization, delivering multiple initiatives in ranking, query understanding, and UX that drove measurable improvements in gross merchandise value (GMV), revenue, and other key business metrics. Successfully launched machine learning-based ranking improvements, query understanding services, and facets, with direct impact on customer success and engagement. Built and scaled the Berlin search team, establishing a high-performing local organization. Led the roadmap, architecture, and design of Query Understanding V1 services, improving search relevance and setting the foundation for future search innovations. Oversaw architecture design, engineering processes, and quality standards across the Search Science organization. Partnered with product leadership to define and execute the AI and search platform roadmap, aligning cross-functional teams to deliver impactful search improvements. Introduced robust engineering practices and culture across a large applied science organization, combining research excellence with product delivery at scale.

Served as Engineering Director for the AI and Science Lab (Megadon Lab) of Recruit Holdings (Japan), overseeing engineering, dev tools, infrastructure, and production deployment across AI initiatives serving over 100 companies within the holding. Built and scaled the engineering organization from the ground up, hiring a high-performing team to support AI research and applied initiatives. Designed and delivered a robust AI infrastructure and CI/CD environment, enabling the research organization to develop and deploy solutions at scale across multiple business units. Led forward-looking long-term AI and scientific development, including conversational AI initiatives, ensuring alignment between research, engineering, and production deployment. Established engineering culture, processes, and best practices, empowering teams to deliver reliable, high-quality AI solutions across the holding. Partnered with executive, research and business leadership to define strategic AI roadmaps, bridging foundational AI science with practical enterprise applications, and enabling measurable business impact across the Recruit Holdings ecosystem.

https://angel.co/company/ozlo/people Co-founded Ozlo, a conversational AI startup focused on building advanced knowledge graph and NLP-driven search and recommendation systems. Played a key role in shaping the company’s strategy, product vision, and AI roadmap, and served on the advisory committee following initial growth. Built and guided the development of the NLP stack, enabling deep document and query understanding for conversational search. Led the design and implementation of the graph search engine, creating a foundational knowledge graph instrumental for search, data modeling, and AI products. Developed data crawling, parsing technologies, and machine learning pipelines, helping bootstrap the company’s natural language processing efforts. Supported the recruitment of the founding AI and engineering team, establishing the technical foundation for scaling the product. Oversaw evaluation of the conversational search engine and aligned engineering and product priorities with strategic goals. Ozlo’s technology and expertise were acquired by Facebook in 2017, contributing directly to their conversational AI initiatives. https://techcrunch.com/2017/07/31/facebook-buys-ozlo-to-boost-its-conversational-ai-efforts/

Led the global engineering, analytics, and search science organization for Walmart Search, spanning walmart.com, Walmart Grocery, Sam’s Club, Asda (UK), and other properties, including teams in Sunnyvale, CA, and Bangalore, India. Oversaw the search engine supporting $17B GMV per year, driving measurable impact across multiple categories and geographies. Successfully launched numerous search features across ranking, query understanding, navigation panels, guidance elements, and search UX, driving up to 25% annual conversion improvements and billions of dollars in revenue impact. Co-designed, built, and launched Walmart Grocery search as a new search vertical, and developed specialized e-commerce search solutions for multiple catalogs, including Electronics, Apparel, and Home, significantly enhancing business performance. Led ML and operations research initiatives for grocery stores, improving in-store operations and efficiency. Introduced learning-to-rank techniques in search, resulting in double-digit revenue improvements, higher average basket size, and better add-to-cart rates. Directed data management, analytics, visualization, and data science services, establishing robust data curation, cleaning, and metrics processes to ensure high-quality customer experiences. Defined and executed the vision, strategy, and roadmap for global search, applying online experiments to evaluate new search ranking algorithms, UX improvements, and browse page optimizations. Partnered with multiple merchandising teams to launch new search verticals, delivering measurable gains across catalogs and enhancing cross-catalog sales, GMV, and consumer satisfaction.

Led the science and NLP efforts for search across App Store, iTunes, Book Store, and other Apple properties, driving double-digit improvements in conversion rates through advanced search ranking, query understanding, and search features. Designed, implemented, and launched core ranking improvements, including text ranking optimizations, anti-fraud measures, and Universal search ranking for heterogeneous content such as apps, books, movies, TV shows, and music—understanding user intent and promoting relevant corpora, resulting in significant revenue uplift. Pioneered query understanding capabilities, including synonyms, NLP-based entity extraction, query topicality, and intent modeling, enhancing the accuracy and relevance of search results across multiple Apple platforms. Designed and launched spell correction for App Store and iTunes, improving user experience by handling typos and fat-finger mistakes. Developed internal tools and frameworks to increase productivity for data scientists and machine learning engineers, enabling more rapid experimentation and deployment of search and ranking improvements.http://techcrunch.com/2013/11/26/improved-app-store-search-engine-now-corrects-for-users-fat-finger-mistakes-other-misspellings/