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Senior AI Engineer - Professional Services - UAE

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Key Responsibilities:

  • Partner with Customers: Collaborate closely with customer stakeholders to understand their business goals, identify high-impact use cases, and define technical requirements for AI solutions.

  • Build & Deploy AI Solutions: Design, develop, and deploy end-to-end AI solutions using the DataRobot platform and open-source tools. This includes:

  • Agentic AI: Developing and deploying agents on DataRobot leveraging common frameworks such as Langgraph, CrewAI, Llama Index

  • Generative AI: Building custom GenAI chatbots, Retrieval-Augmented Generation (RAG) systems.

  • Predictive AI: Developing and deploying classic machine learning models for use cases like forecasting, churn prediction, and fraud detection.

  • Serve as a Technical Expert: 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.

  • Deliver Value: Ensure that the solutions you build are robust, scalable, and directly contribute to the customer's business objectives.

  • Communicate & Collaborate: Clearly communicate complex technical concepts and project outcomes to both technical and non-technical audiences, from data scientists to C-level executives.

Knowledge, Skills and Abilities:

AI & Machine Learning Expertise:

  • Strong proficiency in Python and common data science libraries (e.g., pandas, scikit-learn, NumPy, etc.).

  • Practical experience with Generative AI technologies, including Large Language Models (LLMs), vector databases,

  • 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.

Application Development & Operations:

  • Demonstrable experience developing and deploying applications, including building REST APIs (e.g., using Flask, FastAPI) to serve ML models and GenAI logic.

  • Proficiency with containerization using Docker and experience deploying and managing applications on container orchestration platforms like Kubernetes (K8s).

  • Solid understanding of secure application development practices, including authentication/authorization (e.g., OAuth, API keys), secrets management, and securing public-facing endpoints.

  • Customer Focus: Experience in a client-facing or consulting role with exceptional verbal and written communication skills. You must be comfortable leading technical discussions and presenting to diverse audiences.

  • Problem-Solving Mindset: A deep curiosity and a passion for solving complex, unstructured problems.

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