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Victory N. - Fullstack Developer, Machine Learning, Back-End Development

My journey at Softaims has been defined by curiosity, growth, and collaboration. I’ve always believed that good software is not just built—it’s carefully shaped through understanding, exploration, and iteration. Every project I’ve worked on has taught me something new about how to balance simplicity with depth, and efficiency with creativity. At its core, my work revolves around helping businesses and people achieve more through thoughtful technology. I’ve learned that the most successful projects come from teams that communicate openly and stay adaptable. At Softaims, I’ve had the opportunity to work alongside professionals who challenge assumptions, share knowledge generously, and inspire continuous improvement. I take pride in focusing on the fundamentals—clarity in logic, consistency in design, and empathy in execution. Software is more than a set of features; it’s a reflection of how we think about problems and how we choose to solve them. By maintaining this perspective, I aim to build solutions that are not only effective today but also flexible enough to support the challenges of tomorrow. The culture at Softaims promotes learning as an ongoing process. Every new project feels like a step forward, both personally and professionally. I see each challenge as a chance to refine my skills and contribute to the shared vision of building technology that genuinely improves lives.

Main technologies

  • Fullstack Developer

    3 years

  • Data Science

    2 Years

  • Python

    1 Year

  • SQL

    1 Year

Additional skills

  • Data Science
  • Python
  • SQL
  • Data Analytics
  • AI Chatbot
  • FastAPI
  • Flask
  • OpenAI API
  • LangChain
  • Technical Writing
  • AI Agent Development
  • LLM Prompt Engineering
  • AI Builder
  • Machine Learning
  • Back-End Development

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Potentially possible

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Experience Highlights

Case Radar - A Generative AI Application for Nigerians to know the law

I built RAG pipelines and AI agent workflows to answer user queries efficiently, analysing over 1,000 PDF documents for the knowledge base. I exposed endpoints via FastAPI and managed deployment with a focus on speed and scalability, optimising for high traffic without performance issues.

How to Build RAG Apps with Pinecone, OpenAI, Langchain & Python

I wrote a technical guide on building Retrieval-Augmented Generation (RAG) apps using Pinecone, OpenAI, LangChain, and Python. The goal was to simplify RAG concepts and help developers build production-ready pipelines. I covered vector search, LLM integration, and prompt orchestration with clear code examples. The article has helped many AI engineers and developers quickly grasp and implement RAG workflows.

Sentiment Analysis Website

This project is used to analyse sentences and determine whether a sentence is positive, negative or neutral. This is a display of my Natural Language Processing skills. The backend was built with Flask and deployed on render. https://sentiment-analyzer-app.onrender.com/

How to Add Memory to RAG Applications and AI Agents

I created a technical article on how to add memory to RAG applications and AI agents using LangChain and Python. The goal was to help developers build more context-aware AI systems that can remember and reference past interactions. I covered different memory types like ConversationBufferMemory and showed how to integrate them into RAG workflows. The article has helped AI engineers build more engaging, stateful AI apps.

Education

  • Enugu State University of Science and Technology

    Bachelor of Engineering (BEng) in

Languages

  • English
  • Igbo

Personal Accounts