Artificial Intelligence Engineer

Company DescriptionTalent Bridge is a technology and software development company responsible for the technical execution, development, and engineering of the GoldenTik project. GoldenTik, the parent company and owner of the project, is building an intelligent, fast, and scalable marketplace ecosystem designed for modern multi-vendor e-commerce. Talent Bridge works as the technology and execution partner behind the platform, developing and maintaining its software systems, infrastructure, artificial intelligence capabilities, web applications, mobile applications, and backend services. The GoldenTik platform combines modern software engineering with advanced artificial intelligence, including Large Language Models (LLMs), Natural Language Processing (NLP), Computer Vision, Optical Character Recognition (OCR), Voice AI, Speech-to-Text, Text-to-Speech, Recommendation Systems, Semantic Search, Retrieval-Augmented Generation (RAG), AI Agents, intelligent automation, analytics, and personalization. The ecosystem includes product and inventory management, customizable storefronts, seller and administrator dashboards, secure payment integrations, intelligent search, recommendation systems, analytics, customer communication tools, and AI-powered commerce experiences. Through Talent Bridge’s engineering and AI teams, GoldenTik is developing scalable technology that enables sellers, businesses, and enterprises to manage, automate, and grow their digital commerce operations. Role DescriptionThe Artificial Intelligence Engineer will join Talent Bridge as part of the engineering team responsible for developing and implementing artificial intelligence technologies for the GoldenTik project. This is a full-time, on-site role based in Amman, Jordan. The AI Engineer will design, develop, integrate, deploy, and maintain production-grade AI systems across the GoldenTik ecosystem. The role covers Generative AI, Large Language Models, NLP, Computer Vision, OCR, Voice AI, recommendation systems, intelligent search, machine learning, and intelligent automation. The engineer will collaborate closely with backend, frontend, mobile, DevOps, product, and data teams to transform product and business requirements into scalable and reliable AI solutions. Key responsibilities include: Design, build, train, fine-tune, evaluate, and deploy machine learning and deep learning models.Build LLM-powered applications using commercial and open-source models.Develop Retrieval-Augmented Generation (RAG) systems using embeddings, vector databases, semantic retrieval, reranking, and contextual generation.Develop AI Agents and intelligent workflows capable of interacting with APIs, databases, marketplace services, and internal systems.Build NLP solutions for classification, summarization, translation, information extraction, intent detection, entity recognition, and conversational AI.Develop semantic, hybrid, and personalized search systems using embeddings, ranking, and reranking.Build recommendation and personalization systems for products, stores, sellers, advertisements, and customer experiences.Develop Computer Vision systems for image understanding, object detection, classification, product recognition, visual similarity, moderation, and image analysis.Build OCR pipelines to extract text and structured information from documents, images, invoices, receipts, forms, labels, and product packaging.Develop document understanding solutions combining OCR, Computer Vision, NLP, and LLMs.Build Speech-to-Text systems for transcription, voice commands, multilingual speech processing, and customer interactions.Implement Text-to-Speech and Voice AI solutions for voice assistants, automated support, and conversational applications.Develop real-time conversational AI systems combining speech recognition, LLMs, RAG, tool calling, and voice synthesis.Integrate AI providers and platforms such as OpenAI, Anthropic, Google Gemini, Hugging Face, and other commercial or open-source technologies.Evaluate, optimize, and deploy open-source AI models within the project infrastructure.Develop fraud detection, anomaly detection, risk scoring, and intelligent monitoring solutions.Build AI-powered product enrichment systems for titles, descriptions, categorization, tagging, attributes, SEO content, and visual analysis.Develop multilingual AI capabilities, particularly for Arabic and English.Prepare, clean, process, analyze, and manage datasets used for AI development.Build scalable AI APIs and microservices integrated with GoldenTik’s backend, web, and mobile applications.Optimize AI systems for latency, accuracy, scalability, GPU/CPU utilization, inference cost, and reliability.Monitor production AI systems and continuously improve model performance.Research, benchmark, and implement emerging AI technologies relevant to GoldenTik.Document AI architectures, APIs, models, experiments, datasets, and technical decisions.QualificationsBachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Software Engineering, or a related field, or equivalent practical experience.Strong Python programming skills and solid software engineering fundamentals.Experience with PyTorch, TensorFlow, or similar machine learning frameworks.Strong understanding of neural networks, transformers, embeddings, and modern AI architectures.Hands-on experience with Large Language Models and Generative AI.Experience with models or APIs such as OpenAI, Claude, Gemini, Llama, Qwen, Mistral, DeepSeek, or similar technologies.Knowledge of prompt engineering, structured outputs, function/tool calling, context management, and LLM evaluation.Experience building RAG systems and working with embeddings and vector databases.Familiarity with technologies such as Qdrant, Pinecone, Weaviate, Milvus, pgvector, Elasticsearch, or OpenSearch.Practical experience with NLP and transformer-based architectures.Experience or strong knowledge in Computer Vision and image processing.Familiarity with OpenCV, YOLO, torchvision, Detectron, or similar tools.Experience with OCR technologies such as Tesseract, PaddleOCR, EasyOCR, vision-language models, or cloud OCR solutions.Familiarity with document AI and structured information extraction.Knowledge of Speech-to-Text technologies such as Whisper or equivalent systems.Familiarity with Text-to-Speech, speech synthesis, and Voice AI.Understanding of multimodal AI involving text, images, audio, video, and documents.Experience with SQL and/or NoSQL databases and data pipelines.Familiarity with REST APIs, WebSockets, microservices, and production AI integrations.Experience with Docker, Linux, cloud environments, and containerized applications.Familiarity with GPU workloads, AI model deployment, and inference optimization.Understanding of MLOps, model versioning, experiment tracking, monitoring, and deployment pipelines.Strong analytical, problem-solving, communication, and teamwork skills.Ability to produce reliable, scalable, and maintainable production-quality code.Preferred QualificationsExperience in e-commerce, marketplaces, fintech, search, advertising, or recommendation platforms.Experience with recommendation engines, ranking systems, personalization, or semantic search.Experience with Arabic NLP, Arabic OCR, multilingual LLMs, or Arabic speech recognition.Experience building AI Agents and tool-using LLM applications.Familiarity with LangChain, LangGraph, LlamaIndex, Hugging Face Transformers, vLLM, or similar AI frameworks.Experience with LoRA, QLoRA, PEFT, model fine-tuning, quantization, or inference optimization.Experience deploying AI services using FastAPI, Docker, Kubernetes, or similar infrastructure.Experience with multimodal AI systems.Knowledge of AI safety, moderation, guardrails, hallucination reduction, privacy, and secure AI development.Experience delivering production-grade AI systems is highly preferred.