About

AI architecture across strategy, governance, and production delivery.

Senior AI Architect with 16+ years of enterprise experience building AI, cloud, GRC, and integration platforms. Focused on agentic AI, RAG, MCP-based orchestration, responsible AI governance, and production platform architecture.

Profile

Name
Bhaskar Boruah
Role
Senior AI Architect
Location
Austin, Texas

Professional biography

Bhaskar Boruah is a Senior AI Architect focused on designing and delivering production-grade AI platforms for enterprise environments. He brings 16+ years of experience across AI architecture, cloud-native systems, enterprise integration, governance, risk, and compliance platforms, with work spanning Toyota, USAA, Bank of America, Autodesk, and Expedia.

His current work centers on agentic AI systems, multi-LLM orchestration, retrieval-augmented generation, MCP-based tool-use architectures, model governance, and responsible AI controls. He specializes in translating ambiguous business and governance requirements into deployable platform capabilities: secure data flows, evaluation pipelines, model approval workflows, observability, runtime controls, and scalable cloud infrastructure.

Bhaskar has architected enterprise AI and data platforms on AWS using services such as Amazon Bedrock, OpenSearch, ECS, S3, DynamoDB, RDS, ElastiCache, Lambda, and event-driven integration patterns. His background in GRC and risk systems gives him a practical perspective on trustworthy AI: governance should not live only in documents, but in the control planes, pipelines, and runtime systems that engineering teams operate.

He is currently pursuing a Master of Science in Artificial Intelligence at the University of Texas at Austin, deepening his work at the intersection of applied AI, system architecture, and responsible deployment.

Skills

AI strategy and architectureResponsible AI governanceCloud-native system designModel evaluation and deploymentEnterprise integrationSecurity and risk management

Architecture expertise

Designing cloud-native AI platforms, risk-aware governance frameworks, and production-ready machine learning systems for enterprise delivery.