Zain Ul Abdin

@zainulabdin568

Senior AI Engineer: RAG, AI Agents, fine tuned LLM Solutions, backend, AWS

Paquistão
Inglês
Algumas informações são exibidas no idioma inglês.
Sobre mim
I’m a Senior Generative AI & Full-Stack Engineer specializing in Python, FastAPI, AWS, and production-grade LLM systems. I build scalable AI SaaS apps, APIs, AI agents, RAG pipelines, chatbots, fine-tuned LLM solutions, automation workflows, and cloud deployments using LangChain,LangGraph, OpenAI, Claude,Hugging Face,Docker, Kubernetes, and vector databases. Engineering-first approach: Clean architecture, secure scalable systems, clear documentation, CI/CD, and maintainable code. From MVP to enterprise production, I help businesses ship AI products that drive growth, efficiency, and revenue.... Saiba mais

Habilidades

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zainulabdin568
Zain Ul Abdin
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Conheça meus serviços

Implementação e Implantação de IA
I will build ai agents and multi agent systems using langgraph
A partir deUS$ 100 /projetoMais detalhes
Implementação e Implantação de IA
I will build production ai backend for your ai saas mvp with fastapi docker, kubernetes
A partir deUS$ 100 /projetoMais detalhes

Portfólio

Experiência profissional

Self_Employed

Generative AI Engineer

Self Employed • Freelance

Feb 2020 - Present • 6 yrs 7 mos

Full-stack and machine-learning work from 2020; generative-AI / LLM focus since 2024. 1,830+ hours logged on Upwork across 56+ completed projects (full-stack, ML, and GenAI). 🔷 Build end-to-end GenAI applications: RAG and agentic systems (LangChain, LangGraph, CrewAI), fine-tuned vision-language and language models (LoRA / QLoRA), served behind FastAPI / Flask with React, Streamlit, or Gradio frontends. 🔷 Develop multimodal pipelines combining OCR (Tesseract / Unstructured.io), vision-language models (CLIP, Qwen2-VL, Florence-2), Whisper transcription, and vector search (FAISS, Qdrant, Pinecone, AstraDB). 🔷 Fine-tune and adapt open models for domain tasks — e.g., Florence-2 for document understanding — using PEFT, gradient checkpointing, and 8-bit optimization to train on consumer-grade hardware. 🔷 Containerize and deploy with Docker and GitHub Actions CI/CD to AWS (EC2, App Runner) and single-node Kubernetes; monitor with Prometheus / Grafana. 🔷 Deliver across healthcare / medical imaging, legal, fintech, e-commerce, SaaS, and content domains.