AI Engineer – Databricks & Enterprise Data (SAP Integration)

Role Overview We are seeking an AI Engineer to design and deploy AI-driven solutions using Databricks, with a focus on leveraging enterprise SAP data for finance and analytics use cases. This role involves building production-grade AI/ML systems, developing intelligent chatbots, and implementing agentic AI workflows on top of large-scale data platforms. Key Responsibilities • Design, build, and deploy AI/ML solutions using Databricks (Spark, Delta Lake, MLflow) • Develop scalable data pipelines to ingest and process SAP data (S/4HANA, CDS Views, APIs, Datasphere) • Build and deploy AI-powered applications such as finance chatbots and intelligent assistants • Implement agentic AI workflows that can autonomously interact with enterprise data and systems • Perform feature engineering and data transformation on large datasets • Productionize AI solutions with model serving, monitoring, and optimization • Collaborate with Finance, Analytics, and IT teams to deliver business-driven AI use cases • Ensure data governance, security, and enterprise compliance standards Required Qualifications • 5+ years of experience in AI/ML, Data Engineering, or Applied AI roles • Strong hands-on experience with Databricks (Spark, Delta Lake, MLflow) • Proficiency in Python and SQL • Experience building end-to-end data pipelines and production-grade AI solutions • Experience integrating or working with enterprise data systems (SAP preferred) • Hands-on experience in deploying AI applications (not just models) Preferred Qualifications • Experience building chatbots or conversational AI systems • Exposure to LLMs / Generative AI (LangChain, RAG, etc.) • Experience with agentic AI frameworks or autonomous workflows • Familiarity with SAP data sources (S/4HANA, CDS, Datasphere) • Cloud experience (Azure / AWS / GCP) • Experience in finance or FP&A analytics