Ahmed Faisal

Senior AI Engineer specializing in Agentic AI, Multi-Agent Systems, RAG pipelines, and cloud-native architecture.

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RawalpindiMember since 25 March 2026

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About

As a Senior AI Engineer and Cloud-Native Architect with over 5 years of experience, I specialize in building production-grade AI systems and autonomous solutions. My expertise spans Generative AI and Multi-Agent Systems, where I design Agentic RAG pipelines using frameworks like Lang Chain, Lang Graph, and Llama Index.

I bring deep technical proficiency in Computer Vision (YOLO, SAM3) and Acoustic Intelligence (Sensory AI, STT/TTS), enabling me to create complex, multi-modal applications. On the backend, I architect scalable microservices using Python (Fast API) and Node.js/TypeScript (Nest JS), often leveraging RabbitMQ for event-driven orchestration.

My engineering background is grounded in robust DevOps practices. I have extensive experience deploying cloud-native solutions on Azure (AI Foundry, Copilot) and AWS, utilizing Docker and Kubernetes for containerization and CI/CD pipelines to ensure high-availability delivery.

Experience

As an AI Consultant, I partner with global clients across government, hospitality, and public sectors to transform operational workflows using cutting-edge Agentic AI, LLMs, and Voice AI technologies.

Engineered a Sovereign AI Agent: Built a WhatsApp AI assistant for the government sector to automate public services (trade renewals, suggestion boxes, complaints). Deployed securely via our proprietary platform on Azure (AI Foundry, Container Apps), complying with strict data sovereignty rules.
Architected an AI Voice Platform: Designed a custom voice solution for a hospitality client that autonomously manages phone interactions like multi-item pickup orders and table reservations. Includes a real-time dashboard with live analytics, automated notifications, and seamless human escalation.
Spearheaded Enterprise AI Platform: Led the architecture of an in-house sovereign AI platform empowering organizations to visually build, test, and deploy custom AI Agents. Features an advanced RAG Engine, Workflow Studio, local model deployment, and immutable logs for enterprise auditability and monitoring.
Developed an Omnichannel RAG Desk: Created a chat and voice AI Agent serving as a public sector front desk. Orchestrated multi-agent routing to dynamically handle complaint logging, commercial zoning inquiries, and human handoffs, ensuring hallucination-free responses grounded in approved documents.
Drove Agentic R&D: Researched and implemented next-gen frameworks (OpenClaw, OpenFang) and advanced RAG techniques to optimize response latency and contextual accuracy in production.
Managed Cloud Infrastructure: Leveraged Voice AI platforms (VAPI, Twilio) and scalable cloud infrastructure to deliver secure, multi-tenant enterprise AI solutions.