Databricks AI Engineer
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Requirements
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)