Senior AI Engineer📣 Job Ad

About the Senior AI Engineer Role

Ejada is seeking a Senior AI Engineer to join our team in Riyadh, Saudi Arabia. This full-time role is central to designing, developing, deploying, and optimizing advanced Artificial Intelligence solutions that drive business transformation and innovation initiatives. The successful candidate will provide technical leadership in implementing Machine Learning models, Large Language Models (LLMs), Agentic AI solutions, AI Operations (AIOps), and enterprise-scale AI platforms, ensuring scalability, reliability, security, and measurable business value.

Core Responsibilities

• Design, develop, and deploy AI and Machine Learning solutions to address business and operational challenges.
• Build and optimize Generative AI applications leveraging Large Language Models (LLMs) and enterprise AI frameworks.
• Design and implement Retrieval-Augmented Generation (RAG) architectures using vector databases and knowledge retrieval technologies.
• Develop Agentic AI solutions utilizing multi-agent frameworks and orchestration platforms.
• Build, maintain, and optimize APIs and backend services supporting AI-driven applications.
• Implement and manage AI model deployment, serving, monitoring, and lifecycle management processes.
• Establish MLOps and AIOps best practices to ensure reliable model delivery and operational excellence.
• Design and maintain scalable data pipelines, feature engineering workflows, and AI-ready data architectures.
• Optimize AI inference performance, model serving infrastructure, and resource utilization.
• Collaborate with business stakeholders, data engineers, architects, and technology teams to identify and implement AI use cases.
• Implement monitoring, observability, and evaluation frameworks to track AI model quality, performance, and reliability.
• Support cloud-native AI deployments and infrastructure across public cloud platforms.
• Provide technical guidance, mentorship, and knowledge sharing to engineering teams.
• Contribute to AI strategy, architecture standards, governance practices, and innovation initiatives.

Minimum Qualifications

• Bachelor's Degree in a relevant field.
• Professional certifications in Artificial Intelligence, Machine Learning, Data Science, Data Engineering, or Cloud Platforms.

Required Experience

• A minimum of 5 years of experience in Artificial Intelligence, Machine Learning, Data Engineering, or Software Engineering.
• Proven experience in designing and deploying AI/ML solutions in enterprise environments.
• Hands-on experience with LLMs, Generative AI, RAG-based architectures, MLOps practices, and cloud platforms.

Key Technical Skills

• Proficiency in Python Programming, Advanced SQL, API Development, and integration.
• Expertise in Large Language Models (OpenAI, Azure OpenAI, Hugging Face), Retrieval-Augmented Generation (RAG), Vector Databases (Qdrant, Pinecone, Chroma), LangChain, LangGraph, and Multi-Agent Systems.
• Strong skills in Machine Learning, Advanced Analytics, Kubernetes, Docker, CI/CD Pipelines, MLOps, vLLM, Model Serving, and AI Inference Optimization.
• Experience with Data Engineering Tools (Airflow, Kafka, ETL Pipelines).
• Experience with Cloud Platforms (AWS, Microsoft Azure, Google Cloud Platform).
• Familiarity with AI Monitoring and Evaluation Tools (LangFuse, MLflow, Prometheus, Grafana).
• Knowledge of AI Platform Engineering, AIOps, Enterprise Data Management, and Data Architecture.

Professional Competencies

• Strong analytical and problem-solving capabilities.
• Excellent troubleshooting skills.
• Effective communication and stakeholder management abilities.
• Demonstrated technical leadership.