Mankinde J.

I’m an AI Engineer building production-grade AI agents, RAG systems, LLM applications, machine learning solutions, and computer vision systems. I build production software, not prompt wrappers or demo chatbots. With 8+ years of software engineering and AI experience and Top Rated on upwork, I work with a specialized team ranked among the Top 10 Machine Learning agencies. I build reliable AI systems for real users, data, traffic, and edge cases. AI Engineer | AI Agents | RAG | LLM My core AI engineering work includes: • Retrieval Augmented Generation (RAG) • AI agents, agentic workflows, and multi-agent systems • LLM orchestration, tool calling, and function calling • Structured outputs and schema-based responses • Prompt engineering and optimization • LLM evaluation and benchmarking • Hallucination reduction and grounded generation • Semantic search, vector search, and knowledge bases • Document intelligence • OpenAI, Anthropic Claude, and Google Gemini APIs • LangChain, LangGraph, and LlamaIndex I build AI agents that retrieve information, reason over context, call external tools, execute multi-step workflows, and return reliable results. Production AI needs strong retrieval, evaluation, error handling, observability, scalable APIs, and sound architecture. Machine Learning Engineer | Data Scientist I build machine learning systems for structured, numerical, and time-series data, including demand forecasting, anomaly detection, classification, regression, predictive modeling, biomedical signal analysis, structural health monitoring, feature engineering, and model evaluation. My ML stack includes Python, scikit-learn, pandas, NumPy, SciPy, TensorFlow, PyTorch, and Keras. I build measurable, reproducible models and combine ML with LLMs and AI agents. Computer Vision Engineer | VLM | Multimodal AI I build computer vision and multimodal AI systems: • Object detection and multi-object tracking • Pose estimation and image segmentation • Video analytics and visual inspection systems • Vision Language Model applications • Multimodal AI pipelines I use OpenCV, YOLO, PyTorch, TensorFlow, and VLMs to build systems that understand images and video as well as text. I combine vision, deep learning, LLMs, and agents into production systems that see, interpret, reason, and act. Python Developer | Backend Engineer | Full Stack AI Developer I build production APIs and backend systems using Python, FastAPI, PostgreSQL, Docker, Git, JavaScript, and REST APIs. I work with Pinecone, pgvector, and other vector databases, using LangChain, LangGraph, LlamaIndex, or custom Python architectures. I can own the complete AI product from model development and prompt engineering through backend APIs, databases, vector search, orchestration, integration, testing, and deployment. The goal is a scalable AI product that works in production. Production AI Engineering I build systems with reliable APIs, maintainable Python, logging, monitoring, automated testing, retrieval and LLM evaluation, structured outputs, error handling, fallbacks, context optimization, hallucination mitigation, vector search optimization, scalable services, and production deployment. I approach AI engineering as software engineering: the model is only one part of a reliable, scalable system. Specialized AI Team I work with a specialized team including a Computer Vision PhD, deep learning researchers, and mathematical optimization specialists, allowing us to handle larger AI, ML, computer vision, RAG, and agentic projects. We combine research-level AI expertise with practical software engineering and production architecture. Clients hire me for AI agents, RAG systems, LLM applications, machine learning, forecasting, predictive analytics, computer vision, VLM applications, Python backend development, AI automation, and complete AI products. Main Technology Stack AI/LLM: OpenAI API, Anthropic Claude, Google Gemini, RAG, AI Agents, Agentic AI, Prompt Engineering, Tool Calling, Structured Outputs, LLM Evaluation Frameworks: LangChain, LangGraph, LlamaIndex ML: Python, scikit-learn, pandas, NumPy, SciPy, TensorFlow, PyTorch, Keras Computer Vision: OpenCV, YOLO, Object Detection, Tracking, Segmentation, VLMs, Multimodal AI Backend: FastAPI, PostgreSQL, Pinecone, pgvector, REST APIs Engineering: Docker, Git, JavaScript, API Development, Production Deployment If you need an AI Engineer who understands LLMs, machine learning, computer vision, Python, backend engineering, and production architecture, I can help take your AI product from concept to production with the engineering discipline required to make it work reliably in the real world.