Hosted by IEEE Silicon Valley Blockchain Group, Co-hosted by Blockchain Technical Community, FreeCodingSchool
Speakers: Raj Karan Gunukula (Coinbase), Revanth Reddy Airre (HippocraticAI)

Meeting Date: Thursday, December 18, 2025
Time: Checkin via Zoom for presentation at 6:00 PM (PST)
Cost: none
Format: Technical Talks + Career Discussion
Reservations: events.vtools.ieee.org/m/520440
Summary: This event brings together two focused talks that connect the architecture of AI in Blockchain/Web3 with practical career guidance for professionals entering this fast-growing space. The first talk explores how intelligent systems are designed, evaluated, and governed in blockchain and fintech environments. The second outlines the skills, roles, and pathways for building a successful AI career in the Blockchain ecosystem. Together, they provide a clear view of where the industry is heading and how to prepare for it.

First talk: Orchestrating AI in Web3 and Fintech: The Architecture, Evaluation, and Governance Needed to Build Intelligent Systems that Scale
As AI systems evolve from deterministic software to probabilistic, continually adapting intelligence, deploying them in production raises a unique challenge: how do you preserve “don’t trust, verify” in a world where the model is never exactly the same twice? In this environment, real-world success depends less on model size and more on the orchestration layer that makes AI reliable, safe, and compliant across trading, custody, risk, and customer experiences. This talk explores AI usage in Web3 and digital asset ecosystems, where trust, security, and regulation are first-class constraints. We’ll walk through the integration layers—data infrastructure (including on-chain and off-chain signals), retrieval systems, evaluation pipelines, safety envelopes, and governance mechanisms—that surround the model. Drawing from large-scale, zero-to-one AI initiatives at Amazon and the AI transformation experience at Coinbase, we’ll examine how intelligent systems behave in production, why traditional software patterns fail in high-stakes financial and blockchain environments, and what architectural and organizational frameworks are needed to support rapid iteration without compromising safety or trust. Attendees will learn how to design AI systems where evaluation is always-on, data lineage and provenance (including on-chain data flows) are first-class citizens, and safety is embedded directly into the architecture through policy engines, guardrails, and model-agnostic orchestration layers. We will also discuss practical strategies for building infrastructure that can adapt to rapid model evolution, enable secure experimentation on sensitive financial and blockchain workloads, and ensure that quality, grounding, and behavior remain stable over time, even as both models and fintech space evolves.
Bio: Raj Karan Gunukula is a seasoned technology leader with 14+ years of experience driving large-scale AI, machine learning, and data infrastructure programs across fintech and commerce. He currently serves as Group Technical Program Manager at Coinbase, where he leads AI adoption across the software development lifecycle. Previously at Amazon, Raj rose to Principal TPM, founding and leading a team of TPMs supporting engineers, scientists, and XFN teams to deliver flagship Generative AI and intelligent advisor solutions that scaled to millions of sellers worldwide. His career blends deep technical grounding from his B.Tech. in Electrical Engineering at Indian Institute of Technology (IIT) with hands-on leadership in AI innovation, product scaling, and business transformation.

Second Talk: Building an AI Career in the Blockchain and Web3 Startup Ecosystem
AI is rapidly transforming the blockchain and Web3 ecosystem, from intelligent developer tools and security analytics to on-chain data processing, trading infrastructure, and autonomous agents. Yet for many students and professionals, the career path into this intersection of AI + decentralized technologies is still unclear.
This session provides a practical, experience-based roadmap for building a successful AI career within the blockchain and Web3 space. We will explore the skill sets that matter most (distributed systems, AI/ML foundations, smart contracts, data engineering, and agent-based architectures), common roles across research, infrastructure, platform, agentic integration and product, and how to position yourself for these opportunities. We will also discuss how to leverage open-source contributions, IEEE involvement, hackathons, community leadership, and emerging technologies to stand out in a competitive market. Whether you’re entering the field or looking to transition from traditional software roles, you’ll walk away with actionable guidance, learning paths, and a long-term strategy for growing your career at the convergence of AI and Web3.
Bio: Revanth Reddy Airre is a Staff Engineer at the Silicon Valley AI startup HippocraticAI, a thought leader, and a technology expert with a strong commitment to supporting the broader tech community. He holds a Master’s degree from the University of Illinois Urbana-Champaign. Previously, Revanth worked at the Comcast Silicon Valley Innovation Center, where he helped design and implement large-scale, fault-tolerant distributed systems. He contributed to scaling a major data platform from 1M to more than 70M users, addressing complex infrastructure, distributed-systems, and data-platform challenges. Before moving to the United States, he worked at the Paris-based code analysis startup CAST Software and later contributed to several Silicon Valley startups in both the blockchain and AI domains. He has a strong technical background and extensive experience building technology across startup environments.
As Chair of the IEEE Silicon Valley Blockchain Chapter and an IEEE Senior Member, Revanth leads initiatives in blockchain, cloud computing, and AI/ML, fostering community engagement and collaboration in emerging technologies. He also serves globally with the IEEE Blockchain Technical Community as the Global Student Clubs Coordinator, where he successfully onboarded more than 35 student clubs, strengthening academic partnerships and expanding IEEE’s worldwide blockchain education network.
Revanth served on the Program Committee for the International Conference on Blockchain Research and Applications, contributing to global blockchain research and standards. His expertise spans distributed systems, AI inference infrastructure, large language models, next-generation blockchain platforms, interoperability, scalability solutions, cloud computing, and integrating AI-driven agents to enhance security and efficiency. He started FreeCodingSchool in 2020, a not-for-profit initiative providing accessible coding education through workshops, mentorship, and open learning resources. Additionally, he serves as a conference program committee member, speaker, technology awards judge, career guide, and leader across several non-profit organizations. Through these roles, Revanth actively contributes to the tech ecosystem by reviewing research work, judging technology awards, mentoring early-career technologists, and fostering innovation.