Artificial intelligence engineer

The Group Securities is a well-established investment organization working in the finance industry since 1989, as a company devoted to the stock exchange. It was licensed once Qatar Stock Exchange was founded in 1997 and provides an array of investment services to more than 400,000 investors, with portfolios exceeding QR 100 billion. As brokerage firm, The Group Securities finances margin trading and operates as liquidity provider for the listed shares and ETFs. The company has a paid-up capital worth (QR 1 billion) and has been continuously posting profit since its inception. Besides being licensed by Qatar Financial Market Authority to exercise these activities, The Group Securities is also a member of Qatar Stock Exchange.

Responsibilities: Design, build, and deploy AI agents and agentic workflows that automate and enhance business and financial processes. Develop AI-powered services and systems for the firm and its consumers, with an emphasis on secure, on-premise (self-hosted) deployments. Integrate large language models and other AI algorithms into existing systems and pipelines, including retrieval-augmented generation (RAG), tool/function calling, and multi-agent orchestration. Work alongside team members to improve existing systems, increase efficiency, and embed AI capabilities into current processes. Ensure AI solutions meet the firm's requirements for data privacy, security, and compliance by running models and services within on-premise or private infrastructure.

Skills: 2–4 years of experience working in AI, with a bachelor's degree in computer science or a related field. Strong understanding of AI algorithms, including large language models, agent frameworks, and their inner workings, backed by solid foundations in mathematics and statistics. Hands-on experience building AI agents or agentic applications (e.g., with frameworks like Lang Chain, Lang Graph, Llama Index, or similar). Experience deploying and serving AI models on-premise (e.g., using tools like Ollama, v LLM, or self-hosted inference servers) rather than relying solely on cloud APIs. Proficiency in Python; experience with C++ or Java is a plus. Strong knowledge of handling big data, SQL, and frameworks like Apache Spark. Experience deploying AI services/systems into live production environments. Familiarity with vector databases and embedding-based retrieval. Knowledge of OOP, software development methodology and life cycle, containerization (e.g., Docker), and version control tools (Git). #J-18808-Ljbffr