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Question AnsweringIbrahim Abdulhaqq AI & Backend Developer +2348123854855 [email protected] Self-taught Backend Developer with four years of experience in building scalable platforms and microservices, leveraging advanced AI and machine learning integrations to drive innovative, data-driven solutions. Proficient in both NoSQL and SQL databases, with a specialization in secure 3rd-party AI integrations and generative AI application development. Certified Ethical Hacker (CEH) with robust knowledge in cybersecurity, covering vulnerability analysis, secure coding practices, and network protection. Holds an Advanced Diploma in Software Engineering from Aptech, equipped with skills in cloud computing, web development, and enterprise application development. Expertise in deploying and optimizing generative AI applications, with hands-on experience in retrieval-augmented generation (RAG) pipelines, LangChain, and Hugging Face model integration. Known for effectively balancing technology and business needs, ensuring secure, reliable backend infrastructure and cutting-edge AI capabilities. SKILLS ● Programming Languages: Python, SQL, JavaScript, HTML, Java, C++, C# ● Generative AI & Machine Learning: Generative AI Fundamentals, LangChain, Hugging Face Model Integration, Retrieval-Augmented Generation (RAG) Pipelines, Model Optimization, AI Deployment (Cloud & On-Premise), Supervised & Unsupervised Learning, Reinforcement Learning, Data Preprocessing, Model Training & Deployment ● Cybersecurity:
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Text GenerationReviewed chatbot outputs to assess response quality, helpfulness, accuracy, tone, and logical consistency. The project involved checking whether chatbot responses correctly answered user prompts, followed instructions, avoided hallucinations, and maintained safe and relevant communication. I also compared alternative chatbot responses and selected the most accurate and useful output
TextRLHFEvaluated and ranked AI-generated responses to improve the quality, safety, and usefulness of Large Language Models. The work involved comparing multiple model responses, selecting the better answer, assigning quality scores, identifying factual errors, checking relevance to user prompts, and ensuring responses followed annotation instructions.
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Entity (NER) ClassificationWorked on AI data annotation and evaluation projects focused on improving Large Language Models and Natural Language Processing systems. Tasks included reviewing AI-generated responses for accuracy, relevance, clarity, factual correctness, logical consistency, and compliance with annotation guidelines. Also performed response comparison, ranking, scoring, intent recognition, text categorization, and hallucination detection. Maintained high-quality standards by following detailed project instructions, checking outputs carefully, and ensuring consistent annotation decisions across large volumes of tasks.
TextEntity (NER) ClassificationLabeled and classified search queries based on user intent and category. The work involved identifying what users were trying to achieve from short text inputs, grouping queries into relevant categories, and ensuring consistent application of labeling guidelines. This helped improve search relevance, intent recognition, and NLP model performance.
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Evaluation/RatingPerformed analytical evaluation and quality assessment for NLP-based AI systems. The project involved reviewing AI responses, validating reasoning quality, detecting factual errors, identifying inconsistencies, and checking uncommon or edge-case outputs. I contributed to improving dataset quality by ensuring annotations were accurate, consistent, and aligned with project guidelines.
Bachelors , Computer Science
Backend Engineer & Compliance officer
Backend Developer
