DataRobot
Senior AI Engineer - Professional Services
- Permanent
- Riyadh, Saudi Arabia
- Experience 5 - 10 yrs
Job expiry date: 14/10/2026
Job overview
Date posted
30/08/2026
Location
Riyadh, Saudi Arabia
Salary
Undisclosed
Compensation
Comprehensive package
Experience
5 - 10 yrs
Seniority
Senior & Lead
Qualification
Masters degree
Expiration date
14/10/2026
Job description
In this role you will be at the forefront of the AI revolution as an AI Engineer on DataRobot's Professional Services team, working directly with the company's most strategic customers. You will be a trusted advisor and hands-on builder, translating complex business challenges into cutting-edge AI solutions that deliver tangible business value, designing, building, and deploying a wide range of applications from powerful predictive models to sophisticated Generative AI agents and chatbots. You will collaborate closely with customer stakeholders to understand their business goals, identify high-impact use cases, and define technical requirements for AI solutions. You are responsible for designing, developing, and deploying end-to-end AI solutions using the DataRobot platform and open-source tools, including agentic AI development using frameworks such as Langgraph, CrewAI, and Llama Index, generative AI including custom GenAI chatbots and Retrieval-Augmented Generation systems, and predictive AI including classic machine learning models for forecasting, churn prediction, and fraud detection. You will act as a subject matter expert on the DataRobot platform and modern AI/ML development, guiding customers on best practices for MLOps, model governance, and scaling AI initiatives. In this role you will ensure the solutions you build are robust, scalable, and directly contribute to the customer's business objectives, and you will clearly communicate complex technical concepts and project outcomes to both technical and non-technical audiences, from data scientists to C-level executives.
Required skills
Key responsibilities
- Collaborate closely with customer stakeholders to understand their business goals, identify high-impact use cases, and define technical requirements for AI solutions
- Design, develop, and deploy end-to-end AI solutions using the DataRobot platform and open-source tools
- Develop and deploy agentic AI agents on DataRobot leveraging common frameworks such as Langgraph, CrewAI, and Llama Index
- Build custom GenAI chatbots and Retrieval-Augmented Generation (RAG) systems
- Develop and deploy classic machine learning models for use cases like forecasting, churn prediction, and fraud detection
- Act as a subject matter expert on the DataRobot platform and modern AI/ML development
- Guide customers on best practices for MLOps, model governance, and scaling AI initiatives
- Ensure that solutions built are robust, scalable, and directly contribute to the customer's business objectives
- Clearly communicate complex technical concepts and project outcomes to both technical and non-technical audiences, from data scientists to C-level executives
Experience & skills
- Bring approximately 6 to 8 years of hands-on experience in AI application development, software engineering, machine learning engineering, or a similar role with a proven track record of deploying AI solutions or applications into production
- Hold a Master's Degree or Ph.D. in Computer Science, Statistics, Artificial Intelligence, Engineering, or a related quantitative field
- Demonstrate strong proficiency in Python and common data science libraries such as pandas, scikit-learn, and NumPy
- Show practical experience with Generative AI technologies, including Large Language Models (LLMs) and vector databases
- Demonstrate a solid understanding of the end-to-end agentic AI lifecycle, from building agents in frameworks like LangGraph or CrewAI to at-scale deployment and monitoring
- Show demonstrable experience developing and deploying applications, including building REST APIs using Flask or FastAPI to serve ML models and GenAI logic
- Demonstrate proficiency with containerization using Docker and experience deploying and managing applications on container orchestration platforms like Kubernetes
- Show a solid understanding of secure application development practices, including authentication/authorization such as OAuth and API keys, secrets management, and securing public-facing endpoints
- Demonstrate experience in a client-facing or consulting role with exceptional verbal and written communication skills, comfortable leading technical discussions and presenting to diverse audiences
- Show a deep curiosity and passion for solving complex, unstructured problems
- Have hands-on experience with a major cloud platform such as AWS, Azure, or GCP
- Familiarity with the DataRobot AI Platform is a strong plus
- Demonstrate an understanding of MLOps principles and tools for model CI/CD, monitoring, and governance