Asif Rajwani

Senior Technology Executive

Asif Rajwani

Experienced Senior Technology Executive leading global technology organizations to build and operate mission-critical systems supporting millions of users and billions of dollars in daily transactions.

Currently Head of Strategic Solutions Delivery at CLS Group. CLS Group settles over USD 7.0 trillion in payments daily across 18 major currencies; its centralized CLSSettlement service is the global standard for mitigating settlement risk (Herstatt risk) in FX. Previously held senior leadership roles at Bank of America, Citigroup, Barclays Capital, and Credit Suisse.

Core Expertise

AI & Machine Learning

AWS Certified ML Specialty. Hands-on with LLMs, RAG, agentic workflows, Claude Code, MCP servers, and enterprise AI deployment on Amazon Bedrock.

Cloud Architecture

AWS Solutions Architect (Professional) and Security Specialty. Secure cloud infrastructure, cloud-native migration, and compliance for regulated industries.

Distributed Systems at Scale

Systems supporting millions of users and billions in daily transactions. Event-driven and service-oriented architectures for high-volume platforms.

Web Platforms & APIs

High-performance web platforms serving millions of users and corporate clients. Enterprise API gateways, client portals, HTTP/TLS, identity providers, WAF, and end-to-end web security — from retail banking to global FX infrastructure.

Resilience & Security

Highly available systems with auto-scaling, failover, and disaster recovery. RTO/RPO-driven architecture for critical workloads.

Global Technology Leadership

Leading global engineering organizations across development, cloud migration, and AI adoption. Portfolio planning, budgets, delivery execution, and technology strategy at CLS, Bank of America, Citigroup, Barclays, and Credit Suisse.

Ask me anything

Featured Articles

Featured

AI Roundtable: Why I Built a Deliberation Tool Instead of Another Chatbot

Why a confident, single AI answer can hide real engineering risks, and how forcing models to argue with each other surfaces what the initial answer leaves out.
Featured

Guardrails Without a Gatekeeper: Six Rules for Autonomous LLM Applications

Six practical guardrails for a public LLM chatbot: evaluate outputs, constrain context, verify users, cap cost, choose modest models, and fail safely.
Featured

From Frustration to Workflow: AI-Assisted Development for Real Applications

A practitioner's account of building a production application with AI. It covers the false starts, the workflow that actually works, and the real bugs that AI code review caught before users ever saw them.
Featured

The AI-Native SDLC: From Manual Coder to Strategic Curator

How AI is reshaping the software development lifecycle — not just as a coding assistant, but as a complete architectural shift in how teams plan, build, verify, and ship software. A practical guide for developers, business analysts, architects, and teams responsible for CI/CD in an AI-native organization.
Featured

Securely Integrating LLMs with Proprietary Data Using MCP

A hands-on walkthrough of how Model Context Protocol (MCP) enables AI agents to securely access proprietary real-time data and documents — with architecture, demo setup, and working code.
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