Zohaib Aamer
I'm an AI/ML Engineer specializing in Generative AI solutions, with a focus on building practical, production-ready systems that solve real business problems.
About
I’m an AI/ML Engineer specializing in Generative AI solutions, with a focus on building practical, production-ready systems that solve real business problems.
My core expertise lies in developing conversational AI—from advanced voice agents using Retell AI to intelligent chatbots built with LangChain, Llama Index, and Pydantic AI. I’ve extensively worked with RAG pipelines and fine-tuned LLMs for domain-specific applications, including fine-tuning GPT-4o-mini for automated legal complaint generation.
Some of my notable projects include: an AI-powered telemarketing system with real-time performance analytics, a legal case briefing tool for lawyers combining LLMs with RAG, a voice-enabled medical chatbot for interactive learning, and a visa recommendation system for USA immigration.
- 1 year's experience
- Joined October 2025
Skills· 24
Languages
- UrduAdvanced
- DanishIntermediate
- EnglishAdvanced
Industry experience
- Software & Internet
- Professional Services
- Media & Entertainment
- Education
- Healthcare
Work experience· 9 roles
Medical Voice Chatbot: AI-powered medical learning platform featuring two chatbots (Exam Bot for interactive learning and Patient Bot for medical Q&A) with voice-enabled interfaces; implemented modular RAG-driven architecture, hybrid semantic search, multi-model integration; built frontend with React, backend with Python/FAST API, and integrated OpenAI, Gemini, ElevenLabs, Deepgram, and LiveKit.
Processed and indexed over 14K PDFs via Google Vision OCR; improved throughput with multithreading to reduce processing time; exposed REST endpoints via FastAPI to deduplicate and index files; deployed the solution on Azure and integrated with Google Sheets scripts; built MVP chatbot with a RAG pipeline using Azure Studio and OpenAI for Danish language; integrated with Streamlit and multi-channel deployments.
Processed and indexed 14K PDF files via Google Vision API; implemented multithreading to reduce processing time from 63 hours to 14 hours; exposed endpoints via FastAPI to check duplicates and add new files to the index; deployed on Azure and integrated with Google Sheets scripts; built a voice-enabled medical chatbot frontend using React and streaming tech.
Education
Certifications and awards
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