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.

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Core Expertise

Applied AI & Agentic Systems

AWS Certified ML Specialty. LLMs, RAG, and agentic workflows, with hands-on development across modern AI coding tools. Enterprise AI architecture on Amazon Bedrock, with model and cost selection matched to the task.

AI Security & Evaluation

Model-based code security scanning that proves exploitability and validates fixes. Independent evaluator models, cross-model review, and layered guardrails: context containment, token budgets, and safe failure.

Cloud Architecture

AWS Certified 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, spanning retail banking to global FX infrastructure.

Resilience & Continuity

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. Defining AI-native delivery practices for regulated environments: context governance, automated verification, and audit-ready pipelines. Portfolio planning, budgets, delivery execution, and technology strategy at CLS, Bank of America, Citigroup, Barclays, and Credit Suisse.

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Featured Projects

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AI Roundtable

Live, multi-model LLM debates under distinct roles to expose tradeoffs: streamed dialogue, optional multi-voice audio, and AI-generated imagery.
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AI Chatbot

A self-evaluating public AI chatbot embedded on the homepage, powered by a dual-model (OpenAI + Anthropic) pipeline, server-side rate limiting, Cloudflare Turnstile, and Server-Sent Events (SSE) streaming.
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PDF Utilities

Free, privacy-first PDF tools in the browser. Merge, split, sign, compress, watermark, and more using Web Workers and WebAssembly. No accounts and no cloud storage of your documents.
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Featured Articles

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The Refactor That Passes Every Test

Refactoring feels safe to delegate to an AI because behavior is not supposed to change. A shop-inventory example shows why that is backwards: two AI cleanups both reported every test passing, and that still did not mean nothing changed.
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AI Code Security Scanning: From Alerts to Evidence

Model-based code security scanning replaces pattern-only alerts with a pipeline: threat modeling, adversarial verification, chain analysis, patch generation, and fix validation.
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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.
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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.
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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.
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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.
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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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