AI Engineer - Use Cases & Semantic Layer

Responsibilities

• Design and build end-to-end AI use cases across analytics and business workflows
• Independently query, analyze, and prepare data using platforms such as Databricks or Snowflake (SQL, notebooks, etc.)
• Integrate and activate AI models (including LLM-based solutions) into business use cases
• Work within the data infrastructure to ensure correct and consistent data usage for analytics and AI
• Build AI agents, assistants, and automation solutions on top of enterprise data
• Connect data, models, and business logic into usable solutions (dashboards, agents, assistants, etc.)
• Collaborate with IT and data engineering teams for data access and infrastructure alignment (without owning infrastructure)
• Optimize solutions for performance, scalability, and cost (including compute/token usage)
• Continuously explore and implement new AI capabilities and tools
• Strong hands-on experience with AI/ML and LLM-based solutions
• Proven ability to build end-to-end data + AI use cases independently
• Experience building AI agents or AI-powered applications in production environments
• Experience with Databricks or Snowflake (SQL, notebooks, or similar development environments)
• Strong data skills: querying, transformation, and analysis
• Good understanding of modern data architectures (Lakehouse, cloud environments)
• Experience integrating AI into real-world applications (automation, assistants, analytics)
• Experience with cloud platforms (AWS / Azure / GCP)
• Ability to work independently and drive execution end-to-end

Requirements

• Experience with Databricks specifically, including relevant certifications
• Experience with semantic layers or data modeling
• Familiarity with AI orchestration frameworks (e.g., LangChain)
• Experience working in analytics or data-driven organizations

Additional Information

We are looking for a hands-on AI Data Engineer to join our Analytics team and lead the development and implementation of AI-driven use cases. This role requires strong technical expertise in AI, data, and analytics, with the ability to independently design, build, and deploy solutions - from querying and preparing data to activating AI models and delivering end-to-end use cases. The position operates within the data infrastructure layer, supporting analytics, AI, and ML ingestion and use cases, and focuses on turning data and AI capabilities into practical, scalable business solutions. The ideal candidate has experience building AI agents and deploying AI-powered applications in real-world environments, and can help establish best practices and architecture for scalable AI solutions.

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