The Role As a Databricks AI Engineer, you will deliver end to end GenAI solutions directly to enterprise clients. This is a highly hands on, delivery focused role, not traditional data science, focused on building, deploying, and scaling LLM and RAG applications on the Databricks platform. You’ll work in a client facing capacity, owning projects from initial scoping through to production deployment. Key Responsibilities • Deliver E2E GenAI solutions on Databricks • Build RAG and LLM based applications using enterprise data • Implement vector search and agentic workflows (LangChain, etc.) • Productionise AI systems using CI/CD, MLOps, and cloud pipelines • Work directly with clients to deploy and optimise AI solutions Requirements • 5+ years in AI/ML engineering or data systems • Strong hands on expertise with Databricks (Spark, MLflow, Unity Catalog) • Proficiency in Python and tools such as LangChain, OpenAI, Hugging Face • Experience with Databricks AI Tools (Agent Bricks, GenieAI, MosaicAI) • Experience with vector databases (Pinecone, FAISS, Weaviate, etc.) • Strong cloud and CI/CD experience (AWS, Azure, or GCP) • Excellent communication skills for client facing delivery • Databricks certifications (ML Engineer, GenAI, Data Engineer)