Madan Upadhyay — CEO

Architecting Trustworthy AI for the Next Generation. I am a Responsible AI Architect and Technology Leader with 20+ years of technical experience, specializing in the ethical design and robust governance of Generative AI and Agentic AI systems. My mission is to translate complex AI regulation (EU AI Act, NIST RMF) and ethical principles into practical, repeatable engineering practices. For the past seven years, I have worked across the full AI lifecycle—from data science and machine learning engineering to robotic process automation (RPA) and compliance. I excel at bridging the gap between Legal/Compliance, Data Science, and Engineering teams to build sustainable, high-impact AI. My Core Value Proposition: I don't just draft policy; I embed AI Governance directly into the MLOps pipeline. This "shift-left" approach ensures compliance, mitigates systemic bias, and accelerates time-to-market for high-stakes AI applications. Key Achievements & Impact: •Risk Mitigation: Spearheaded the development of an AI Governance Framework for GenAI and agentic systems that reduced legal and reputational risk by 45% ahead of major regulatory deadlines. •Fairness & Explainability (XAI): Architected and implemented a suite of fairness tools that reduced algorithmic bias by 30% in critical agentic applications, securing crucial regulatory approvals. •Operational Excellence: Orchestrated MLOps pipelines with automated data privacy controls, reducing model drift by over 25% within six months for higher system reliability and lower operational costs. •Proactive Strategy: Led AI Red Teaming and proactive risk assessments for high-stakes use cases (e.g., financial advisory agents), avoiding a potential $5M+ in remediation and reputational damage pre-deployment. Skills Responsible AI / Ethics - Generative AI Governance, AI Ethics, Agentic AI Oversight, AI Risk Management, Red Teaming, Algorithmic Bias, Explainable AI (XAI), AI Safety, Data Ethics, Fairness Assessment Strategy & Compliance - EU AI Act, NIST AI Risk Management Framework (RMF), AI Governance Frameworks, MLOps (Ethical Integration), Strategic Planning, Stakeholder Management, Ethical Impact Assessment, Policy Development Technology - MLOps, Python, TensorFlow, PyTorch, Large Language Models (LLMs), Cloud Computing (AWS, Azure, GCP), Data Science, Machine Learning, RPA Automation, CI/CD I am passionate about building the guardrails for innovation. Let's connect to discuss how we can secure your GenAI roadmap and operationalize the future of responsible, trustworthy AI.

Stackforce AI infers this person is a Responsible AI Architect specializing in Generative AI governance and compliance.

Location: Pune, Maharashtra, India

Experience: 20 yrs 4 mos