Lead Digital Solutions Analyst - Data Science

Client of Eram Talent; Eastern Province; Presencial; SAR 400.000 - 650.000; Jornada completa

Descripción de la vacante

Client of Eram Talent seeks an experienced Lead Digital Solutions Analyst to advance AI initiatives and contribute to next-generation AI solutions. The role focuses on AI modules, scalable data pipelines, and real-time data processing, ensuring robust backend infrastructure and model inference capabilities.

You will design scalable backend systems, apply microservices and agentic AI architectures, and collaborate across teams to deliver sovereign AI technologies including LLMs and vision models.

Formación

• Bachelor's degree in Graphic Design or equivalent qualification.
• Minimum 10 years of relevant professional experience in graphic design, data science, AI technologies, or a related field.
• Experience in AI solution development, data pipelines, or AI technology implementation.
• Knowledge of backend infrastructure, real-time data processing, and event-driven architectures.
• Familiarity with microservices, agentic AI architectures, and scalable AI applications.
• Understanding of data preprocessing, transformation, feature engineering, and data storage.
• Exposure to Large Language Models, time-series models, or computer vision technologies is an advantage.
• Strong analytical, problem-solving, and collaboration skills.

Responsabilidades

• Develop and implement AI modules, pipelines, solutions and services for advanced AI technologies.
• Design and develop scalable backend infrastructure to support real-time data ingestion, AI model inference and user access.
• Build real-time data processing components using event-driven architecture.
• Apply microservices and agentic AI architectures to support scalability and flexible system development.
• Develop data pipelines for data preprocessing, normalization, labelling, transformation, feature engineering and storage.
• Support research and development initiatives for sovereign AI technologies including Large Language Models, Large Time-Series Models and Large Vision Models.
• Collaborate with cross-functional teams to develop, integrate and optimize AI-driven solutions.

Conocimientos

AI technologies

Data pipelines

Real-time data processing

Microservices

Agentic AI architectures

Scalable AI applications

Collaboration

Problem solving

Educación

Bachelor's degree in Graphic Design

Herramientas

Backend infrastructure

Event-driven architectures

Large Language Models / time-series / vision models exposure

Descripción del empleo

We are seeking an experienced Lead Digital Solutions Analyst to support advanced AI technology initiatives and contribute to the development of next-generation AI solutions The successful candidate will work on AI modules scalable data pipelines backend infrastructure and real-time data processing systems supporting the development of Large Language Models LLMs Large Time-Series Models and Large Vision Models

Key Responsibilities

• Develop and implement AI modules pipelines solutions and services for advanced AI technologies
• Design and develop scalable backend infrastructure to support real-time data ingestion, AI model inference and user access
• Build real-time data processing components using event-driven architecture
• Apply microservices and agentic AI architectures to support scalability and flexible system development
• Develop data pipelines for data preprocessing normalization labelling transformation feature engineering and storage
• Support research and development initiatives for sovereign AI technologies including Large Language Models Large Time-Series Models and Large Vision Models
• Collaborate with cross-functional teams to develop integrate and optimize AI-driven solutions

Bachelor's degree in Graphic Design or an equivalent qualification, as specified for the position. Minimum 10 years of relevant professional experience in graphic design, data science, AI technologies, or a related field. Experience in AI solution development, data pipelines, or AI technology implementation. Knowledge of backend infrastructure, real-time data processing, and event-driven architectures. Familiarity with microservices, agentic AI architectures, and scalable AI applications. Understanding of data preprocessing, transformation, feature engineering, and data storage. Exposure to Large Language Models, time-series models, or computer vision technologies is an advantage. Strong analytical, problem-solving, and collaboration skills.