AI Engineer - FDE (Forward Deployed Engineer)

Experteer Overview As an AI Forward Deployed Engineer at Databricks, you will develop advanced GenAI solutions and lead production rollouts for customer-facing applications. You will act as a technical advisor, collaborating with product and engineering teams to influence roadmaps and deliver impactful AI outcomes. Your work spans cross-functional engagements, customer-facing engagements, and presenting at industry events to showcase our GenAI capabilities. This role offers hands-on experimentation with state-of-the-art AI tech and meaningful customer impact in a dynamic, learning-driven environment. Pay / Benefits * Develop cutting-edge GenAI solutions using the latest Databricks AI research to solve customer problems * Own production rollouts of GenAI applications for customers and internal uses * Serve as a trusted technical advisor to customers across domains * Present at conferences (e.g., Data + AI Summit) and contribute as a thought leader * Collaborate cross-functionally with product and engineering to influence priorities and the product roadmap Tasks * Experience building GenAI apps (RAG, multi-agent systems, Text2SQL, fine-tuning) with HuggingFace, LangChain, DSPy * Proven expertise deploying production-grade GenAI applications with evaluation and optimizations * Hands-on data science experience with pandas, scikit-learn, PyTorch, etc. * Experience building production ML deployments on AWS, Azure, or GCP * Graduate degree in a quantitative discipline or equivalent practical experience * Ability to communicate technical concepts to diverse audiences * Willingness to travel ~every 4-8 weeks Key requirements *

Pay product and engineering to influence priorities and the product roadmap Tasks * Experience building GenAI apps (RAG, multi-agent systems, Text2SQL, fine-tuning) with HuggingFace, LangChain, DSPy * Proven expertise deploying production-grade GenAI applications with evaluation and optimizations * Hands-on data science experience with pandas, scikit-learn, PyTorch, etc. * Experience building production ML deployments on AWS, Azure, or GCP * Graduate degree in a quantitative discipline or equivalent practical experience * Ability to communicate technical concepts to diverse audiences * Willingness to travel ~every 4-8 weeks Key requirements *