09/26/2026 updated
100 % available
Full-Stack AI Engineer | Backend Developer
Kamoke, Pakistan
Only remote
Bachelor of Science, Computer ScienceAbout me
Full-Stack AI/LLM Engineer with 4+ years of experience building production AI systems. Specialized in GenAI integration, RAG pipelines, and agentic AI architectures. Founder of VulnGuard AI You can also DM me via email at iamhammaddev03@gmail.com if I do not respond here.
AI AgentsRAGLLMJavaScriptArtificial IntelligencePython (Programming Language)Machine LearningNatural Language ProcessingOpenStackBlockchainTensorFlowAzure Machine LearningNext.jsSystems IntegrationTypeScript
AI/ML & Deep Learning
Expertise in PyTorch, TensorFlow, Keras, Scikit-learn, and Hugging Face for building and deploying deep learning models. Proficiency in neural network architecture design, LLM fine-tuning, transfer learning, computer vision, and prompt engineering for production-grade AI systems.
LLM Integration & Multi-Agent Systems
Hands-on experience integrating Claude API, OpenAI (GPT-4, Embeddings), Groq, and Deepgram into intelligent systems. Building multi-agent architectures with tool-calling patterns, RAG systems using Pinecone vector databases, and agentic workflows for complex reasoning and decision-making.
Full-Stack Development
Strong command of the MERN stack (React, Node.js, Express, MongoDB) combined with FastAPI and GraphQL backends. Delivery of high-performance, real-time UIs with WebSocket streaming, REST/GraphQL APIs, and AI-optimized frontends using Next.js 14 and TailwindCSS.
Cloud & DevOps / MLOps
Practical experience with AWS (EC2, S3, Lambda), Docker, Kubernetes, and GitHub Actions CI/CD pipelines. Model serving, infrastructure as code, and deployment on GPU-optimized infrastructure for low-latency inference.
Databases & Data Management
Proficiency in MongoDB, PostgreSQL, Redis, SQLite, and vector databases. Strategic database indexing, query optimization, connection pooling, and schema design for high-concurrency systems serving 200K+ concurrent users.
Computer Vision
Building end-to-end computer vision systems using CNN architectures (ResNet, DenseNet, MobileNet), Vision Transformer (ViT), and transfer learning. Real-time inference, image classification, segmentation, and object detection with GPU-optimized deployment.
Natural Language Processing
Experience with transformer models, BERT/GPT fine-tuning, embeddings and semantic search, NLP pipeline design, text classification, and sentiment analysis for production NLP applications.
Model Explainability & ML Operations
Application of Grad-CAM, LIME, and SHAP for model interpretability and explainability. Hyperparameter tuning, feature engineering, ML pipeline orchestration, and model monitoring for production ML systems.
Programming Languages
Fluency in Python, TypeScript, JavaScript, and SQL for building scalable backend services, AI pipelines, and full-stack web applications.
Expertise in PyTorch, TensorFlow, Keras, Scikit-learn, and Hugging Face for building and deploying deep learning models. Proficiency in neural network architecture design, LLM fine-tuning, transfer learning, computer vision, and prompt engineering for production-grade AI systems.
LLM Integration & Multi-Agent Systems
Hands-on experience integrating Claude API, OpenAI (GPT-4, Embeddings), Groq, and Deepgram into intelligent systems. Building multi-agent architectures with tool-calling patterns, RAG systems using Pinecone vector databases, and agentic workflows for complex reasoning and decision-making.
Full-Stack Development
Strong command of the MERN stack (React, Node.js, Express, MongoDB) combined with FastAPI and GraphQL backends. Delivery of high-performance, real-time UIs with WebSocket streaming, REST/GraphQL APIs, and AI-optimized frontends using Next.js 14 and TailwindCSS.
Cloud & DevOps / MLOps
Practical experience with AWS (EC2, S3, Lambda), Docker, Kubernetes, and GitHub Actions CI/CD pipelines. Model serving, infrastructure as code, and deployment on GPU-optimized infrastructure for low-latency inference.
Databases & Data Management
Proficiency in MongoDB, PostgreSQL, Redis, SQLite, and vector databases. Strategic database indexing, query optimization, connection pooling, and schema design for high-concurrency systems serving 200K+ concurrent users.
Computer Vision
Building end-to-end computer vision systems using CNN architectures (ResNet, DenseNet, MobileNet), Vision Transformer (ViT), and transfer learning. Real-time inference, image classification, segmentation, and object detection with GPU-optimized deployment.
Natural Language Processing
Experience with transformer models, BERT/GPT fine-tuning, embeddings and semantic search, NLP pipeline design, text classification, and sentiment analysis for production NLP applications.
Model Explainability & ML Operations
Application of Grad-CAM, LIME, and SHAP for model interpretability and explainability. Hyperparameter tuning, feature engineering, ML pipeline orchestration, and model monitoring for production ML systems.
Programming Languages
Fluency in Python, TypeScript, JavaScript, and SQL for building scalable backend services, AI pipelines, and full-stack web applications.
Experience
Professional experience0 - 5 years
Freelancer since2021
Languages
EnglishFluent
Project history
End-to-end security analysis platform for Solidity code. Next.js 14 frontend with Monaco Editor for syntax-highlighted contract input, real-time streaming vulnerability detection UI, severity classification, and PDF audit report generation. Node.js backend orchestrating Claude API for intelligent analysis and structured response formatting. Analyzes 15+ vulnerability types in under 10 seconds. Accessible to 10K+ Web3 developers. Stack: Next.js, Node.js, Claude API, MongoDB.
Engineering production AI systems handling 500K+ monthly API requests at under 200ms latency. Designing and implementing LLM integration patterns, real-time inference pipelines, and scalable ML backends. Optimizing neural network models for production deployment, implementing structured logging and distributed tracing. Building multi-agent AI systems using Claude API with tool-calling architectures. Full-stack feature ownership from model inference to user-facing AI-powered UIs.
Multi-tenant architecture serving 200K+ concurrent users. Role-based access control (RBAC), isolated data models, secure routing. Optimized for scale: under 100ms query response times via strategic indexing, connection pooling, Redis caching. Node.js + Express + MongoDB stack.