As an AI Engineer on our Professional Services team, you will be at the forefront of the AI revolution, working directly with our most strategic customers. You'll be a trusted advisor and hands-on builder, translating complex business challenges into cutting-edge AI solutions that deliver tangible business value. This is a unique opportunity to design, build, and deploy a wide range of applicationsfrom powerful predictive models to sophisticated Generative AI agents and chatbots. If you thrive on solving real-world problems and want to work with the latest in AI technology, this role is for you.
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 platform and open-source tools. This includes:
- Agentic AI: Developing and deploying agents on 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 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.
Qualifications
- Experience: 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.
- Education: A Master's Degree or Ph.D. in Computer Science, Statistics, Artificial Intelligence, Engineering, or a related quantitative field.
- Cloud Experience: Hands-on experience with a major cloud platform (AWS, Azure, or GCP).
- Experience: Familiarity with the DataRobot AI Platform is a strong plus.
- MLOps Knowledge: Understanding of MLOps principles and tools for model CI/CD, monitoring, and governance.
Required Skills
- 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.
