AI Engineer
# AI Engineer **Arabic.AI** · Egypt · `Remote` · `Full Time` 💼 **Уровень роли:** `Mid-level` 🕒 **Статус:** *Опубликовано: сегодня* · *Источник: Himalayas (JSON API)* --- ### Top Skills & Match 🎯 **Ключевой стек роли:** `[AI-Engineer]` `[Machine-Learning-Engineer]` `[AI-ML-Engineer]` `[NLP-Engineer]` `[Deep-Learning-Engineer]` `[Artificial-Intelligence-Engineer]` `[AI-Engineering-Specialist]` `[Python-AI-Engineer]` `[AI-Agent-Engineer]` --- ### About the Role Job Purpose As an AI Engineer at Tarjama&, you will be responsible for supporting the design, development, and deployment of agentic and multimodal AI solutions leveraging language, vision, and speech technologies. You will contribute to building scalable, production-ready AI products by assisting in model integration, evaluation, optimization, and data pipeline preparation. You will collaborate closely with senior Requirements Duties & Responsibilities AI Agentic Workflows & Frameworks Design and implement AI agentic workflows that orchestrate language, vision, and speech models for multi-step tasks. Build and extend task-driven, tool-using AI agents using modern agent frameworks and orchestration patterns. Implement decision logic, memory strategies (short-term and vector-based), and tool-calling mechanisms in production-ready systems. Improve agent reliability through structured prompting, planning strategies, and basic error-handling mechanisms. Multimodal AI Development (Text, Vision, Speech) - Develop and integrate text-based AI systems, including LLM pipelines, embeddings, rerankers, and RAG architectures. - Build document understanding pipelines using OCR and vision-based models to extract structured insights from complex documents. - Develop and optimize speech-based AI solutions, including STT, TTS, and conversational voice interfaces. - Design and improve multilingual and translation pipelines with attention to performance and quality. - AI Product Development & Deployment - Own the development of specific AI components or features from design through deployment. - Deploy, monitor, and optimize AI systems in production with guidance on scalability and cost-efficiency. - Collaborate with engineering teams to integrate AI components into maintainable and scalable systems. - Implement logging, monitoring, and basic observability practices to track system performance. - Model Evaluation & Optimization - Define and apply evaluation metrics for AI systems, including accuracy, latency, and robustness. - Benchmark and optimize models for inference performance and cost-efficiency. - Run experiments and A/B tests to validate improvements and support data-driven decisions. - Identify common failure modes and contribute to improving model robustness and reliability. Data Processing & Pipeline Support - Design and maintain data pipelines for text, document, and audio data across training and inference workflows. - Ensure data quality and consistency in collaboration with data teams. - Analyze model outputs and user interactions to support iterative system improvements. Cross-Functional Collaboration - Collaborate with product managers, designers, and engineers to translate requirements into scalable AI solutions - Partner with senior engineers on system design while independently handling well-scoped components. - Support integration, testing, and deployment of AI systems in production environments. Documentation & Knowledge Sharing - Maintain clear documentation for AI pipelines, agent workflows, and evaluation processes. - Contribute to team knowledge sharing through code reviews, demos, and technical discussions. - Follow and help reinforce best practices for AI development and deployment. Originally posted on Himalayas
- AI-Engineer
- Machine-Learning-Engineer
- AI-ML-Engineer
- NLP-Engineer
- Deep-Learning-Engineer
- Artificial-Intelligence-Engineer
- AI-Engineering-Specialist
- Python-AI-Engineer
- AI-Agent-Engineer
Наблюдалась 2026-10-18, впервые 2026-10-18, источник — Himalayas (JSON API).