Ahmed Raza
@ahmedraza7
I build secure AI systems—LLMs, RAG, and automation pipelines—with strong focus on privacy and reliability.
What I'm looking for
I’m a Software & AI Developer specializing in secure AI architectures, Large Language Models (LLMs), and automated data pipelines. I’ve led production AI development for government entities (FBR), with a strong emphasis on data privacy, mitigating LLM vulnerabilities like prompt injection, and deploying robust containerized solutions.
In my recent roles, I designed scalable AI architectures and automated Python pipelines for advanced medical imaging models using PyTorch and the Hugging Face ecosystem, including Docker-based production deployments. I also engineered a secure, production-grade Retrieval-Augmented Generation (RAG) system for complex tax law analysis, building APIs that integrate vector databases and embeddings while applying efficient fine-tuning (LoRA/PEFT) to meet strict business and terminology constraints.
Experience
Work history, roles, and key accomplishments
Remote Operations Specialist
Avantduo Technology Services
May 2026 - Present (1 month)
Designed and maintained scalable Python data pipelines and automated workflows, ensuring strict data consistency and reliability across internal systems. Integrated secure digital tools via REST APIs to reduce manual processing time.
Deep Learning Engineer
RiseTech
Nov 2025 - May 2026 (6 months)
Designed and deployed scalable AI architectures and automated Python data pipelines for medical imaging models using PyTorch and the Hugging Face ecosystem. Implemented strict data preprocessing and Docker-based container deployments to ensure production-grade performance for sensitive training inputs.
Software Developer
Elexoft Technologies
Mar 2025 - May 2025 (2 months)
Developed cross-platform applications and integrated RESTful APIs within secure backend environments. Troubleshot software architectures using Git for version control and optimized system performance.
LLMs & RAG Project Lead
Federal Board of Revenue (FBR Insights)
Jan 2024 - Jan 2025 (1 year)
Engineered a secure, production-grade Retrieval-Augmented Generation (RAG) system for complex tax law analysis with privacy and regulatory compliance. Evaluated and adapted foundation models using LoRA/PEFT and built APIs integrating vector databases and embeddings into the enterprise architecture.
Education
Degrees, certifications, and relevant coursework
Pak-Austria Fachhochschule Haripur
Bachelor of Science, Computer Science
Activities and societies: Relevant coursework: Machine Learning; Data Structures & Algorithms; Digital Logic Design; Computer Architecture; Information Security.
Earned a B.S. in Computer Science, with coursework covering machine learning, information security, and computer architecture; graduated in Jan 2025.
Availability
Location
Authorized to work in
Job categories
Skills
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