[Hiring] AI Engineer @Arabic.AI

Role Description

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 engineers.

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.