AI Engineer

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Lucidya | لوسيديا

WebsiteLinkedInAll Job Openings

51 - 200 employees

🤖 Artificial Intelligence

🤝 B2B

☁️ SaaS

💰 $6M Series B on 2022-01

Artificial Intelligence • B2B • SaaS

Lucidya is a company specializing in social media and online platform analytics. They provide tools and insights that help businesses understand customer sentiment, track brand reputation, and make data-driven decisions. Lucidya's solutions are tailored for engaging with the Arabic-speaking market, leveraging AI technology to process and analyze data for optimal marketing strategies.

📋 Description

• Design, develop, and deploy AI-driven solutions that solve real-world business challenges. • Work across the full AI lifecycle—from data preparation and model development to deployment, monitoring, and optimization. • Collaborate closely with product managers, software engineers, and domain experts. • Own the end-to-end AI lifecycle, including data exploration, model development, evaluation, deployment, monitoring, and continuous improvement. • Perform model evaluation, error analysis, and performance optimization to ensure reliability and accuracy. • Develop and enhance AI applications powered by Large Language Models (LLMs). • Build Retrieval-Augmented Generation (RAG) systems, semantic search solutions, and AI assistants. • Work with embeddings, vector databases, and modern AI orchestration frameworks. • Evaluate and improve model outputs for quality, relevance, latency, and user experience. • Deploy and maintain AI services in cloud and containerized environments. • Build scalable APIs and inference pipelines for real-time and batch processing workloads. • Monitor AI systems in production and troubleshoot performance or reliability issues. • Collaborate with engineering teams to integrate AI capabilities into customer-facing products. • Partner with Product, Engineering, Data, and Customer Success teams to translate business requirements into AI solutions. • Contribute to technical discussions, design reviews, and AI best practices. • Stay up to date with emerging AI technologies and recommend practical innovations that create business value.

🎯 Requirements

• 2–4 years of professional experience in Artificial Intelligence, Machine Learning, Data Science, or related engineering roles. • Proven experience developing and deploying AI or machine learning solutions into production environments. • Strong proficiency in Python. • Experience with machine learning and deep learning frameworks such as PyTorch or TensorFlow. • Solid understanding of machine learning fundamentals, model evaluation techniques, and performance optimization. • Experience building AI applications using Large Language Models (LLMs). • Familiarity with Retrieval-Augmented Generation (RAG), embeddings, and vector search concepts. • Experience building APIs using FastAPI, Flask, or similar frameworks. • Understanding of software engineering best practices, version control, and testing methodologies. • Experience deploying AI models into production environments. • Familiarity with Docker and cloud platforms such as AWS, Azure, or GCP. • Understanding of monitoring, observability, and AI system reliability. • Strong analytical and problem-solving abilities. • Excellent communication and collaboration skills. • Ability to work effectively in a fast-paced, cross-functional environment. • Preferred Qualifications • Experience with LangChain, LangGraph, LlamaIndex, or similar AI orchestration frameworks. • Experience working with vector databases such as Pinecone, Qdrant, ChromaDB, Weaviate, or FAISS. • Exposure to agent-based AI systems and workflow automation. • Experience with MLOps practices, CI/CD pipelines, and model monitoring. • Experience with computer vision, multimodal AI, recommendation systems, or NLP applications. • Familiarity with self-hosted open-source models and modern inference frameworks.