Jr AI Engineer

Learn by building. The Junior AI Engineer supports the development and maintenance of our AI solutions, focusing on data preparation, configuration, testing, and automation within our Azure ecosystem. They contribute to the operational excellence of our workflows while growing into an independent engineer capable of leading small solutions

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You Will

• Prototype & Support: Implement and refine proof-of-concept AI solutions under guidance—especially around data ingestion, model testing, pipeline automation using Azure AI Services and Azure AI Foundry components. 
• Data Preparation: Clean, label, and structure unstructured data (text, PDFs, images) for model ingestion and Resource-Augmented Generation (RAG) workflows, building embeddings or retrieval indexes as needed. 
• Prompt & Tool Development: Assist in creating and tuning prompts, function calls, skill definitions, and service integrations for enterprise-grade GPT/Copilot and Foundry‐based agent applications. 
• Evaluation & QA: Support testing of model outputs, participate in red-team exercises, validation of responses, monitoring for compliance and quality, and help refine evaluation dashboards. 
• Documentation: Maintain versioned records of model configurations, prompt templates, evaluation results, and pipeline documentation to support reuse and transparency. 
• Learning & Collaboration: Engage in continuous learning around AI engineering best practices, cloud development, Azure AI services, Foundry mechanics, and Responsible AI principles. Participate in team knowledge-share and collaboration. 
• We seek Rebels who are curious about AI and its power to transform how we operate and serve our members.
• Actively support the achievement of SCAN’s Vision and Goals.
• Other duties as assigned.

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Your Qualifications

• Bachelor's Degree or equivalent experience preferred
• Foundational understanding of LLM concepts, prompt engineering, vector databases, and how Azure AI Services work.
• Basic proficiency in Python (or similar), REST APIs, JSON schemas, and workflow automation tools (Logic Apps, Power Automate, n8n, etc.).
• Familiarity with Azure AI Foundry fundamentals (model catalog, agent service, connections to Azure AI Services) is a strong advantage.
• Strong curiosity, initiative, and ability to absorb feedback in a fast-moving, experimental environment.
• Commitment to Responsible AI practices—understanding transparency, traceability, and nice to have basic bias/fairness awareness. 
• Collaborative spirit; able to support multiple initiatives and interface with business, analytics, and engineering teams.