class AIEngineer:
def __init__(self):
self.name = "Munawwar"
self.role = "AI Engineer"
self.specialties = ["RAG Systems", "AI Agents", "LLM Optimization", "ASR"]
self.tools = ["LangChain", "LlamaIndex", "Transformers", "Vector DBs"]
def solve_problems_with_ai(self, challenge):
solution = apply(self.specialties, challenge)
return optimize_for_production(solution)I design and implement intelligent solutions by combining foundational ML knowledge with cutting-edge LLM techniques. With expertise in developing generative AI systems, RAG pipelines, and AI-driven knowledge bases, I focus on bridging research advances and practical business applications.
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Built a sophisticated RAG system using embeddings, vector search, and reranking for precise document Q&A |
Developed an LLM-powered system that generates therapy notes from session transcripts |
| Mental Health Diagnostic App Developing an AI-powered mental health assessment tool |
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| RAG Systems Building advanced retrieval systems with reasoning capabilities |
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| Agent Systems Developing autonomous AI agents with planning capabilities |
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| Learning Deep diving into LangGraph, multimodal models, and embedding techniques |
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"AI systems should be robust, transparent, and built to solve real problems. My goal is to create solutions that bridge cutting-edge research with practical applications."
- RAG Expert: Specialized in designing retrieval systems with context processing
- Agent Developer: Build autonomous AI systems with planning and reasoning capabilities
- ASR Specialist: Experience with speech recognition systems and audio processing
- LLM Optimization: Proficient in fine-tuning, prompt engineering, and deployment