AI Engineer

• Develop, deploy and maintain AI-enabled backend services and APIs.
• Build, deploy, and manage AI and data workflows using Databricks, including use of Databricks Asset Bundles for environment-aware deployments.
• Integrate and consume Large Language Models (LLMs) (e.g. Gemini, Claude, GPT) for use cases such as summarization, classification, retrieval-augmentedgeneration (RAG), and conversational AI.
• Collaborate with product, data, and platform teams to translate business requirements into scalable AI solutions.
• Support model integration, API testing, logging, monitoring, and performance optimization.
• Follow secure coding practices and contribute to documentation to support governance, handover, and audit readiness.

Job Requirements

• Hands‑on experience with Python for backend and AI‑related development.
• Experience working with Databricks, including notebooks, jobs, and deployment using Databricks ...