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DataRobot is looking to solve complex business challenges for their strategic customers by translating them into cutting-edge AI solutions that deliver tangible business value, ranging from predictive models to Generative AI agents and chatbots.

Requirements

• 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.
• 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.
• Hands-on experience with a major cloud platform (AWS, Azure, or GCP).

Responsibilities

• Design, develop, and deploy end-to-end AI solutions using the DataRobot platform and open-source tools.
• Developing and deploying agents on DataRobot leveraging common frameworks such as Langgraph, CrewAI, Llama Index
• Building custom GenAI chatbots, Retrieval-Augmented Generation (RAG) systems.
• Developing and deploying 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, guiding customers on best practices for MLOps, model governance, and scaling AI initiatives.
• Ensure that the solutions you build 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.

Other

• Collaborate closely with customer stakeholders to understand their business goals, identify high-impact use cases, and define technical requirements for AI solutions.
• 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.
• A deep curiosity and a passion for solving complex, unstructured problems.
• Approximately 6-8 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.