Atul Gupta

Background

About Atul Gupta

AI & Technical Leadership Deeply Technical Executive & Execution-First Engineering Leader with 20+ years of experience specializing in the design and delivery of Scalable Platforms and Generative AI solutions. Proven track record across startups, MNCs, and high-growth digital product environments. Core Expertise: Applied Generative AI, Agentic AI & ML Engineering For the past several years, I have focused intensely on Applied Generative AI, building and deploying sophisticated systems powered by Large Language Models (LLMs) including GPT-4, Claude, Mistral, and AWS Bedrock. Key AI competencies include: Agentic AI & Multi-Agent Systems: Prototyping and deploying AI Agents to automate complex workflows, decision-making, and achieve long-horizon goals. RAG (Retrieval-Augmented Generation) Pipeline Development: Designing and implementing robust RAG architectures for enhanced context and factuality. Prompt Engineering & Optimization: Developing advanced strategies for model instruction, few-shot learning, and performance tuning. Automated Evaluation Frameworks: Creating measurable, continuous evaluation systems for LLM outputs (e.g, faithfulness, toxicity, coherence). MLOps Tools: Expertise with Hugging Face ecosystem for model discovery, fine-tuning, and deployment. Engineering Leadership & Delivery My strength lies at the intersection of deep Technical Experimentation and Strategic Communication. I rapidly prototype new AI capabilities, thoroughly debunk vendor claims through proof-of-concept development, and share clear, actionable insights to drive responsible AI adoption at scale. I have successfully led significant Engineering Transformations (GuruQ, Rippl, ClassUp), built High-Performance Tech Teams from the ground up, and delivered mission-critical solutions at Global Scale (Fiserv, Clear2Pay, CSC). I thrive on autonomy and delivering immediate, measurable results. Currently Exploring Seeking AI-First Leadership Roles (e.g, Head of AI, VP of Engineering, Director of Applied ML/GenAI) that demand deep technical rigor, strategic autonomy, and demonstrable public impact in the generative AI space.