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aqil_awan

Aqil Awan

@aqil_awan

LLM Engineer Agentic AI Multi Agent Systems

Pakistan
English, Urdu
About me
I’m an LLM Engineer who builds AI solutions that save businesses time, reduce manual work, and improve customer service. I can build: • AI customer support that answers customers 24/7 • Document chatbots for PDFs and company documents • Automation for emails, bookings, and repetitive tasks • AI assistants that find information and complete tasks • AI reporting tools that analyze business data • Custom AI tools to solve your business problems Tell me what you want to improve or automate, and I’ll build the right AI solution for your business. ... Read more

Skills

a
aqil_awan
Aqil Awan
Offline • 
Average response time: 1 hour

See my services

AI Implementation & Deployment
I will build a rag chatbot trained on your business documents
From$25 / projectMore details
AI Implementation & Deployment
I will build ai agents and automate your workflow using claude code
From$20 / projectMore details

Work experience

Ministry_of Defense

LLM Engineer

Ministry of Defense • Full-time

Feb 2026 - May 2026 • 3 mos

RLHF-Based Agentic AI for Military Decision Support • Developed an RLHF training pipeline using Proximal Policy Optimization (PPO) to improve tool selection policies for AI-assisted military decision support systems while reducing incorrect or unnecessary tool invocations by 31 %. • Designed custom reward functions to optimize tool invocation accuracy, agent decision quality, and multi step operational reasoning. • Evaluated agent performance using task success rate, tool precision, and failure analysis to iteratively improve reliability, safety, and decision consistency. • Technologies: Python, PyTorch, Hugging Face Transformers, TRL, PPO, RLHF, MCP. Multi-Agent RAG Knowledge Assistant • Built a multi-agent RAG assistant indexing 40 vehicle manuals (10,000+ pages, 35,000+ chunks) with PostgreSQL/PGVector, achieving 0.89 Answer Relevancy and 0.91 Faithfulness (RAGAS). • Implemented document ingestion, semantic retrieval, reranking, Arize Phoenix evaluation, and FastAPI deployment. (Crew AI, Ollama, PostgreSQL, PGVector, FastAPI). Multi-Agent Legal Decision Support System • Built an AI-powered legal reasoning system of Military Law that simulated plaintiff, defence, and judge agents to generate evidence-based legal arguments and reasoned judicial decisions using Retrieval-Augmented Generation (RAG). • LangGraph-based multi-agent workflow with FAISS-powered semantic retrieval. Integrated Open AI API for low-latency inference and orchestrated multi-step reasoning across specialized AI agents. (LangGraph, FAISS, Groq API, RAG, TypedDict)