Job description

The Staff / Senior AI Engineer (Video AI & LLM Systems) role at Lucidya operates within the artificial intelligence software and B2B SaaS customer experience intelligence industry, focusing on building next-generation multimodal AI capabilities that extend the company’s CXM platform into advanced video intelligence. Lucidya is an AI-native customer experience platform that manages entire customer lifecycles autonomously, from initial engagement through retention and growth, using proprietary Natural Language Understanding (NLU) capabilities trained on millions of multilingual conversations. The platform empowers marketing, support, customer experience, and research teams to deliver personalized experiences that improve customer satisfaction, retention, and lifetime value. This role contributes to a major strategic product direction: expanding the platform’s capabilities beyond traditional social and enterprise data analysis into comprehensive video intelligence. The engineer will design and build systems capable of understanding sentiment, context, and intent across multimodal inputs including visual signals, audio signals, and text data extracted from video content. Responsibilities include architecting end-to-end video analysis pipelines integrating Computer Vision, Video Analysis, and Large Language Models to extract semantic meaning from multimodal content. The position also involves owning the deployment, operation, and optimization of self-hosted LLM infrastructure to comply with Saudi data regulations requiring private model hosting environments. This includes implementing containerized deployment strategies using Docker and Kubernetes across cloud or on-premise infrastructure, managing inference pipelines, and optimizing performance factors such as latency, scalability, reliability, cost efficiency, and uptime. The role requires building production-grade ML systems that operate reliably beyond experimental notebooks, including full lifecycle ownership of modeling, infrastructure, deployment, and monitoring processes. As a senior technical contributor, the engineer influences architecture decisions, engineering standards, and system reliability while mentoring mid-level and junior engineers and providing technical guidance through code reviews and architecture discussions. The position operates in a fast-paced engineering environment where engineers collaborate with Product teams to define technical roadmaps, translate conceptual ideas such as video listening capabilities into deployable product features, and continuously deliver measurable improvements to enterprise customer experiences. Additional technical exposure areas may include Arabic multimodal NLP, OCR for Arabic text within video content, generative video models or diffusion models, and Edge AI optimization techniques. Success in the role is measured by deployed production systems and real-world feature adoption rather than experimental research output, requiring strong expertise in machine learning engineering, multimodal systems integration, and large-scale production AI deployment.