Kathan Joshi
Agentic AI Systems | AI Architecture | Python & AWS | LLM & RAG Applications
- Role
- Vice President at JPMorganChase
- Location
- Mumbai, MH, IN
- LinkedIn followers
- 500 followers
About Kathan Joshi
I design and build agentic AI systems and advanced RAG applications at scale—solutions that reason, act, and collaborate to solve complex business problems. By combining Python-based development on AWS with modern agentic frameworks and Model Context Protocol (MCP), I bridge the gap between AI architecture and production-grade software.I currently architect AI-native applications that move beyond chat-based interfaces to autonomous, goal-driven execution. My work sits at the intersection of AI architecture, machine learning, and data platforms, where I translate abstract requirements into scalable, enterprise-ready solutions.With a background in data science and analytics engineering, I bring a systems-level perspective to AI—ensuring that models, agents, RAG pipelines, and orchestration layers work together reliably, responsibly, and with high retrieval accuracy.Core Interests & Expertise:Agentic Design Patterns: Multi-agent systems and autonomous orchestrationAdvanced RAG & Data Integration: High-precision retrieval across structured and unstructured dataEnterprise AI Architecture: Scaling AI/ML solutions across complex cloud environments (AWS)Governance & Observability: Evaluation, monitoring, and reliability for LLM-based systemsI value robustness over hype and focus on building AI systems that deliver measurable impact beyond compelling demos.If you’re building or scaling the next generation of agentic AI platforms, let’s connect.
Experience
Vice President
Feb 2025 — Present · Mumbai, IN
Education
Dharmsinh Desai University
Bachelor of Engineering (B.E.), Electronics and Communication
2005 — 2009
Skills
- Analytics
- C
- Java Enterprise Edition
- Pl/Sql
- Integration
- Databases
- Oracle
- Requirements Analysis
- Sql
- Business Intelligence
- Data Migration
- Data Warehousing
- Obiee
- Data Modeling
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