Executive Summary

Strategic AI Leadership: 8 years of combined experience spanning AI/ML development, project management, and enterprise solution delivery, including 6 years in end-to-end AI/ML architecture and 4+ years in team management, leading solution architecture, and engineering roles, driving enterprise-scale implementations of LLMs, agentic AI systems, and multi-agent conversational platforms with direct team leadership responsibilities.

Proven Delivery at Scale: Spearheaded 75+ AI/ML initiatives across NLP, computer vision, predictive modeling, and deep learning—delivering real-world impact across industries, including 15+ production-grade deployments using GPT, LLaMA, and Gemma models with advanced RAG pipelines.

Expert in Cloud-Native AI & Compliance: Architected, deployed, and optimized AI systems on major cloud platforms (Azure, GCP, AWS), leveraging microservices, scalable containerized infrastructure, and full regulatory compliance for high-stakes environments including banking and finance.

Current Focus: Leading cross-functional teams in enterprise-grade LLM agent-based solutions and multi-agent orchestration systems for clinical research and commercial applications.

Core Technical Competencies

AI Chatbot Architecture & Strategy
  • Enterprise chatbot design, conversational AI strategy
  • Multi-agent orchestration, agentic AI frameworks
  • LangChain, LangGraph, Semantic Kernel
  • Intent recognition, entity extraction, prompt engineering
LLM Engineering & Fine-tuning
  • GPT model suites, Gemini, Gemma, Llama
  • Hugging Face ecosystem, LoRA fine-tuning
  • RAG (Retrieval-Augmented Generation), hybrid search
  • Token cost optimization, hallucination reduction
Machine Learning & Deep Learning
  • TensorFlow, PyTorch, Keras, Scikit-learn
  • Predictive modeling, time series forecasting
  • CNNs, RNNs, Transformers, ensemble methods
  • Computer Vision: OpenCV, YOLO, object detection
Cloud & DevOps
  • Azure (OpenAI, ML), GCP (Vertex AI), AWS (SageMaker)
  • Docker, Kubernetes, CI/CD pipelines
  • MLOps, LLMOps, microservices architecture
  • API integration, distributed systems
Programming & Tools
  • Python, C++, C#, .NET, JavaScript, SQL
  • NLP, sentiment analysis, NLP-to-SQL conversion
  • Statistical modeling, data engineering
Specialized Applications
  • Banking & Financial AI, regulatory compliance
  • Medical AI, autonomous systems
  • GANs, synthetic data generation
  • Business automation, process optimization

Professional Experience

AI Project Manager and Engineer (Mar 2025 – Current)

Marshall Clinical Research Consulting, Remote, Alberta

  • Leading cross-functional teams in architecting enterprise-grade LLM agent-based chatbot solutions for commercial and clinical research applications.
  • Spearheading development of multi-agent orchestration systems with deep learning algorithms and human-like psychiatric chatbot/avatar voice bot capabilities.
  • Architecting multi-agent AI systems with complex orchestration frameworks for clinical decision support.
  • Managing stakeholder relationships and translating clinical requirements into AI chatbot architectures with regulatory compliance.
AI Research Associate (Nov 2024 – Current)

Durham College - AI Hub, Oshawa, ON, Canada

  • Delivered 15+ enterprise AI/ML projects across banking, healthcare, automotive, and industrial domains.
  • Led AI-centered R&D initiatives encompassing chatbot solutions, computer vision systems, and predictive analytics.
  • Managed a team of 15-20 professionals, supporting cross-functional collaboration and knowledge transfer.
  • Established MLOps/LLMOps best practices including CI/CD, deployment, monitoring, and compliance frameworks.
AI/ML Engineer (Sep 2024 – Jan 2025)

INQ Consulting, Toronto, Canada

  • Architected and delivered 7+ enterprise AI/ML solutions for telecom and compliance sectors.
  • Specialized in designing production-grade AI chatbot systems and privacy risk assessment platforms.
  • Developed real-time risk scoring engines using fine-tuned LLMs with 95% compliance review time reduction.
  • Implemented enterprise AI governance frameworks with automated compliance monitoring.
AI/ML Project Lead & Solution Architect (Jan 2020 – Dec 2023)

F5 Systems, India

  • Progressed from AI-ML Software Analyst to Project Lead, delivering 56+ AI/ML projects for fintech, pharmaceutical, and enterprise clients.
  • Directed end-to-end AI solution delivery from strategic planning to deployment, spanning conversational AI and predictive analytics.
  • Orchestrated deployment of scalable AI solutions across multi-cloud ecosystems (Azure, GCP, AWS).
  • Led development of financial forecasting platforms using time series analysis and advanced statistical modeling.

Key Technical Projects

Last Updated: June 2025
Banking AI Chatbot
Enterprise Banking AI Chatbot & Process Automation

Architected end-to-end LLM-based agentic commercial chatbot integrated into comprehensive banking applications. Automated 85% of customer service queries through intelligent multi-agent architecture with money transfers, loan applications, and predictive financial insights.

Autonomous Vehicle
Autonomous Vehicle Perception & AI Decision System

Led development of real-time AI decision-making system for autonomous vehicles integrating computer vision, deep learning, and sensor fusion. Achieved significant latency reduction via CUDA optimization for General Motors partnership.

Privacy Risk Assessment
AI-Driven Privacy Risk Assessment Chatbot

Designed real-time conversational risk scoring engine using fine-tuned LLMs with intelligent chatbot interface for compliance teams. Reduced compliance review time by 95% through automated analysis for Telus.

Financial Forecasting
ML-Powered Financial Forecasting & Customer Targeting

Led development of comprehensive machine learning suite for financial performance forecasting and customer segmentation using time series analysis, regression, and clustering algorithms for LIC.

Medical Photo Analysis
Medical Photo Analysis & LLM Recommendation System

Developed automated patient photo classification system with AI-driven conversational interface for personalized clinical recommendations using computer vision and NLP techniques for Facetech.

EGSTREE
End-to-End General AI Decision Support System (EGSTREE)

Architected agentic ecosystem with specialized AI agents for data fusion, complex task resolution, and strategic recommendations. Implemented agent-based simulations for scenario planning and business automation insights.

Research & Publications

  • Self-Aware Neural Networks (SANN) - Internal research development underway
  • LLMs in Substance Use Treatment Applications - Co-authoring paper with University of Alberta
  • Conversational AI Ethics and Bias Mitigation - Contributing researcher on healthcare applications

Client Portfolio: Academic institutions (University of Waterloo, Durham College), telecom (TELUS), automotive (General Motors), government insurance (LIC), hazardous goods institutions, pharmaceutical companies, and multiple healthcare/enterprise clients.

Education

Durham College, Oshawa, ON

Post-Graduate Certificate: Artificial Intelligence Analysis, Design, and Implementation

Post-Graduate Certificate: Project Management

M.S University, Baroda, IN

Bachelor of Engineering

Contact

Email: thakkarvatsal13@gmail.com

Phone: 647-897-2937

LinkedIn: linkedin.com/in/vatsal-thakkar13

Portfolio: vatsalthakkar1326.github.io