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Qasim Javid

@qasimjavid1

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NLP Engineer at Wanclouds building MCP servers and LLM applications for enterprise automation.

Pakistan

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At Wanclouds, I design and deploy Model Context Protocol servers that enable zero-prompt automation for NLP models, including IBM Logging MCP, Zabbix MCP, and Kubectl Command Generator MCP.

I built CloudWhisper Chatbot to connect OpenAI, Claude, and knowledge graphs with IBM VPC+ backup and restore APIs. I also developed RAG pipelines with LlamaIndex and Qdrant, delivering 95% accurate NLP responses.

As a Senior Backend Developer at Wanclouds, I optimized AWS and GCP resource use and helped reduce costs by 20% or more. Earlier, I automated telecom reporting at Nokia and developed an AI-based brain tumor detection system at Slosh AI Solutions.

Experience

Work history, roles, and key accomplishments

Current

NLP Engineer

Current

Wanclouds

Jan 2023 - Present (3 years 10 months)

Designed and deployed MCP servers for zero-prompt automation, fine-tuned LLMs, and built AI chatbots with knowledge graphs. Implemented RAG pipelines and cost optimization analytics, reducing costs by 15-20%.

Python MCP LLM Fine tuning LLaMA 2 Claude GPT Knowledge Graphs RAG LlamaIndex Qdrant fastAPI Docker Redis PostgreSQL OpenAI IBM Cloud Zabbix

Current

Senior Backend Developer

Current

Wanclouds

Sep 2021 - Present (5 years 2 months)

Optimized cloud resource utilization, refactored backup/restore architectures, and automated EKS scaling. Integrated BigQuery for cost tracking and designed multi-cloud discovery APIs.

AWS GCP Amazon EKS Karpenter MGN BigQuery Redis SQL Python Docker Kubernetes Cloud Architecture Cost Optimization

RAN & Automation Engineer

Nokia

Apr 2021 - Sep 2021 (5 months)

Automated telecom reports with Python, reducing generation time to under 30 seconds. Monitored 2G/3G/4G network alarms and produced operational summaries.

Python Automation Telecommunications Network Monitoring Reporting

Python Engineer

Slosh AI Solutions

Jul 2020 - Feb 2021 (7 months)

Developed AI-based brain tumor detection using ANTSpy and UNET models achieving 95% dice score accuracy. Improved MRI preprocessing pipelines and processed BraTS datasets.

Python ANTSpy U Net Medical Imaging MRI BraTS Deep Learning

Education

Degrees, certifications, and relevant coursework

FAST National University of Computer and Emerging Sciences

Bachelor of Engineering, Computer Engineering

2016 - 2020

Bachelors in Computer Engineering from FAST National University of Computer and Emerging Sciences, Islamabad, Pakistan (2016-2020). Final year project involved Arduino-based sign language gloves converting gestures into audio/visual outputs.