Viktor A.

About Viktor A.

AI Product Manager and data science leader with 10+ years managing analytics teams at Fortune 500 companies (Deloitte, Accenture, General Dynamics) and large-scale government enterprises. Currently leading global teams of 20+ data scientists and ML engineers at Deloitte, building next-generation AI search products that process 100K+ documents with 70% improvement in search relevance.Proven track record in Generative AI transformation: Pioneered enterprise RAG systems and LLM adoption across person organizations as strategic advisor to Chief Data & Analytics Officer. Drove $10M investment in AI/ML infrastructure through executive presentations demonstrating 300% ROI via GenAI-powered automation.Global Leadership Excellence: Built and scaled globally distributed teams across North America and Europe, establishing 24/7 operations and cross-cultural collaboration frameworks. Led end-to-end GenAI product development conducting 50+ user interviews and implementing multi-agent AI systems that reduced research time by 50%.• Architected production GenAI systems using LangGraph agents and RAG architecture• Established GenAI Center of Excellence and trained 200+ professionals on responsible AI practices• Built MLOps pipelines with A/B testing frameworks for continuous model improvement• Automated 40% of analytical workflows through strategic GenAI implementation• Early AI/ML adopter with experience implementing NLP and deep learning before the GenAI-eraCore Expertise: Generative AI & LLMs | Python, SQL, Neo4j | Machine Learning & NLP | Cloud Platforms (AWS)| Vector Databases & Embeddings | MLOps & Model Deployment | Global Team Leadership | Product Analytics | Executive Advisory

Experience

1. Ai Product Manager

   Deloitte

   Oct 2024 — Present · Tampa, FL, US

   Architected production GenAI system using LangGraph agents and RAG architecture, processing 100K+ documents with 70% improvement in search relevanceImplemented multi-agent AI system with specialized LLMs for query understanding, document retrieval, and response generation, reducing research time by 50%Led end-to-end GenAI product development conducting 50+ user interviews, defining product roadmap, creating wireframes, and prioritizing features based on user feedback and market analysisBuilt MLOps pipeline for continuous model improvement, implementing A/B testing framework for GenAI features with automated performance monitoring

Education

• University of Michigan - School of Information

  M.S., Applied Data Science

  2019 — 2021

• Carnegie Mellon University

  Certification, Chief Data Officer

• Metro State University

  B.S, Business/Marketing

  2005 — 2012