Abdul Muqtadir Mohammed
Senior Engineer AI/ML @Amazon
Austin, Texas, United States
Actions
I am a results-driven engineer with over 11 years of experience architecting transformative solutions at the intersection of AI/ML, distributed systems, and cloud computing. My career has been defined by solving complex technical challenges, delivering high-impact innovations, and leading cross-functional teams to drive measurable business outcomes.
🌍 Building Logistics at a Planetary Scale
At Amazon, I’ve had the honor of working at the epicenter of one of humanity’s most complex logistical undertakings—a global delivery network that moves billions of packages annually, connects millions of customers. I’ve architected AI/ML solutions for solving and optimizing routing and planning and continuing to improve benchmarks across the industry.
💡 Open-Source Advocate & Industry Contributor
My commitment to innovation extends beyond proprietary systems—I’m passionate about building tools that empower the broader tech community. As an AWS Open-Source Champion, I’ve advanced critical projects like the Terraform AWS Provider and Jenkins Plugin for EC2 Fleet, helping organizations streamline CI/CD and cloud resource management. My work has been adopted by industry leaders like Apple and HashiCorp, proving that open collaboration drives progress.
🌐 Global Expansion & Infrastructure Leadership
I’ve played a pivotal role in AWS’s global growth, automating region deployments and reducing setup time from years to weeks. By designing secure, scalable infrastructure for high-security applications, I’ve supported AWS’s expansion into regions like LCK for U.S. government applications, ensuring compliance and reliability at every step.
🔥 Co-Founder & CTO at Butternut AI
Entrepreneurship is in my DNA. As CTO of Butternut AI, I’ve co-created an AI-driven platform that allows users to generate fully functional websites in seconds—democratizing web development for non-technical audiences. By enabling 400,000+ website creations, I’ve proven that vision, execution, and scalability can coexist in a fast-paced startup environment.
Area of Expertise
Topics
Integration of next GenAI in Supply Chain
The integration of next-generation Artificial Intelligence (GenAI) technologies into supply chain management is transforming traditional operations into intelligent, adaptive ecosystems. This paper explores how GenAI—encompassing large language models (LLMs), generative design, autonomous agents, and advanced predictive analytics—is being leveraged to enhance decision-making, improve demand forecasting, optimize logistics, and increase supply chain resilience. Through real-world case studies and technical insights, we demonstrate how GenAI enables real-time data interpretation, automates complex workflows, and augments human expertise in areas such as procurement, inventory management, and last-mile delivery. The paper also discusses the challenges of adoption, including data governance, integration with legacy systems, and ethical considerations. Ultimately, the research underscores that the strategic deployment of GenAI is not merely an innovation layer but a foundational shift toward hyper-intelligent, agile supply chains.
Transforming Logistics with Foundation Models
Foundation models are no longer just for language—they're becoming the brains behind smart logistics. In this session, we dive into how LLMs are used for anomaly detection, route optimization, and supply-side forecasting. Attendees will learn how these models ingest structured and unstructured data, reason across systems, and enable predictive, autonomous logistics at scale.
Abdul Muqtadir Mohammed goes over how Foundation models can be brains behind smart logistics
Autonomous Supply Chains with GenAI Agents
This talk focuses on building autonomous supply chain systems using GenAI agents. By combining LLM reasoning with reinforcement learning and real-time telemetry, these agents can autonomously adjust inventory levels, reroute deliveries, and manage disruptions. Discover the underlying infrastructure and how multi-agent systems are being used to create agile, self-correcting supply networks.
From Data to Decisions: GenAI in Fulfillment
Fulfillment is where supply chain complexity hits the real world. This session shows how GenAI bridges data and decisions—turning shipment logs, demand signals, and customer behavior into live operational plans. See how LLMs drive decisions in picking, packing, routing, and customer updates, with minimal human input.
Abdul Muqtadir Mohammed
Senior Engineer AI/ML @Amazon
Austin, Texas, United States
Actions
Please note that Sessionize is not responsible for the accuracy or validity of the data provided by speakers. If you suspect this profile to be fake or spam, please let us know.
Jump to top