Brij Kishore Pandey
Principal Engineer & Architect - Ai @Wells Fargo
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WORK HISTORY
Principal Engineer & Architect - Ai @Wells Fargo
Charlotte, NC, US
Enterprise AI ArchitectureDesigning scalable and secure AI platforms across the bank’s global footprint, with a focus on reliability, governance, and enterprise standards.Generative AI & Agentic SystemsArchitecting production-grade GenAI solutions, including LLM-powered applications, RAG-based systems, and agentic workflows, applying multi-agent orchestration and AI governance frameworks to real-world financial use cases.Classical ML & Hybrid AIDesigning hybrid AI architectures that combine classical machine learning models (classification, forecasting, anomaly detection) with LLM-based reasoning layers to deliver explainable and auditable outcomes.Cloud & Data Engineering (GCP)Building secure, cloud-native architectures on GCP and Azure, integrating modern data platforms to support ML, GenAI, and analytics workloads at scale.Architecture LeadershipCollaborating with product, engineering, security, and business teams to align enterprise AI strategy with technical execution and measurable business impact.
EDUCATION
SRM University
Bachelor of Technology (B.Tech.)
SKILLS
ABOUT BRIJ KISHORE PANDEY
Disclaimer:All views are strictly my own. I do not speak on behalf of my employer. My content focuses on publicly available knowledge, frameworks, and industry trends that help advance the developer and AI community. Who I am: AI Architect with 16+ years building AI systems — from classical ML to Generative AI to Agentic architectures — in regulated, production environments at enterprise scale. I design end-to-end AI platforms: RAG pipelines, multi-agent orchestration, autonomous workflows, model governance — alongside the classical ML foundations (regression, classification, time-series forecasting, anomaly detection) that still power most real-world decisions. My work spans cloud architecture (AWS, Azure, GCP), MLOps, data engineering, and cross-functional leadership — aligning AI strategy with actual execution. What I share here: 700K+ developers and AI practitioners follow along as I break down the tools, architectures, and frameworks shaping the AI engineering space. I publish cheatsheets, infographics, and practitioner-level content on: → Agentic AI — multi-agent systems, orchestration, tool calling, autonomous workflows → LLM infrastructure — RAG, evaluation, prompt engineering, production deployment → AI architecture — system design, platform engineering, governance at scale → Classical ML — the fundamentals that still matter Everything I share comes from building, not just reading. If you\'re an engineer, architect, or leader trying to make sense of the AI stack — I make the complex stuff clear, visual, and actionable.
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