Artificial Intelligence Engineer | Hybrid - QC/Makati

Role Overview:

• Work set-up: Hybrid 3x / RTO 2x per week | Eton, Centris
• Work shift: Nightshift

This role focuses on building and deploying AI/ML solutions within enterprise data ecosystems. Key responsibilities include developing ML models and GenAI/LLM solutions (RAG, prompt engineering), integrating AI into data pipelines and platforms like Fabric and Databricks, ensuring production readiness (monitoring, performance), translating AI outputs into business insights, and upholding Responsible AI governance—all within an Agile delivery framework.

Technical Skills span:

• ML Engineering: model lifecycle, feature engineering, training/deployment
• Cloud AI & Data Platforms: Azure AI/OpenAI, Microsoft Fabric, Databricks (MLflow, Delta Lake), Lakehouse architecture
• Data Engineering: Python/SQL, pipelines, orchestration
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