AI Engineer (2x onsite)
# AI Engineer (2x onsite) **S3** · Makati · `On-site` 🕒 **Статус:** *Опубликовано: 12 дней назад* · *Источник: Indeed* --- ### About the Role AI Engineer (Hybrid 2x a week onsite) - Design, build, and deploy AI/ML solutions that integrate with enterprise data products, pipelines, and lakehouse architectures. - Develop and operationalize machine learning models and AI services for use cases such as predictive analytics, anomaly detection, and automation. - Design and implement Generative AI solutions using LLMs , including RAG architecture and prompt engineering. - Collaborate with data engineers to embed AI capabilities into data pipelines and ensure seamless integration with data platforms (e.g., Fabric, Databricks ). - Partner with product owners, architects, and stakeholders to translate business needs into AI-driven solutions and reusable components. - Enable AI readiness across DL&I data products by standardizing model integration, feature engineering, and inference patterns. - Ensure AI solutions are production-ready by implementing monitoring, logging, and performance optimization practices. - Support integration of AI outputs into data products, dashboards, and business processes, ensuring interpretability and usability. - Work with analytics and reporting teams to translate model outputs into business-facing insights and metrics. - Contribute to enterprise AI governance by ensuring compliance with Responsible AI principles (fairness, transparency, accountability). - Document AI models, features, pipelines, and assumptions to support reuse, auditability, and knowledge sharing. - Participate in Agile delivery practices including backlog refinement, sprint planning, and continuous improvement. Technical Skills: AI & Machine Learning Engineering - Machine learning model development and lifecycle management - Feature engineering, model training, evaluation, and deployment - Familiarity with supervised and unsupervised learning techniques - Experience with model serving and inference pipelines Cloud AI & Data Platforms - Azure AI services ( Azure Machine Learning, Cognitive Services, OpenAI integration ) - Microsoft Fabric AI capabilities ( Copilot, AutoML, intelligent insights ) - Databricks ( MLflow, Model Registry, Delta Lake ) - Understanding of Lakehouse architecture and AI integration patterns Data Engineering & Integration - Strong Python and/or SQL for data processing and model integration - Experience with data pipelines and orchestration tools - Knowledge of data transformation and feature pipelines - Integration of AI outputs into downstream analytics systems MLOps & Deployment - CI/CD pipelines for machine learning models - Model versioning, monitoring, and retraining strategies - Logging, observability, and performance tuning of AI solutions Delivery & Tooling - Azure DevOps (ADO) for backlog and work tracking - Git-based source control for code and model artifacts - Experience with collaborative development workflows Domain Knowledge: - Understanding of enterprise data platforms and lakehouse architectures - Familiarity with IT operational data and enterprise analytics use cases - Experience with ServiceNow, its architecture, and data - Awareness of data governance, data quality, and compliance considerations - Experience with integrating AI solutions into enterprise workflows and systems - Understanding of c - Exposure to enterprise-scale data environments and performance considerations Soft Skills: - Strong problem-solving and analytical thinking, with a structured and detail-oriented approach - Ability to translate complex technical concepts into business-relevant insights - Effective communication across technical and non-technical stakeholders - Strong collaboration skills across product, engineering, and architecture teams - Influencing skills to promote AI adoption and data-driven practices - Strong documentation and knowledge-sharing discipline - Continuous learning mindset, especially in rapidly evolving AI technologies - Comfortable working in Agile , fast-paced delivery environments Pay: Php150,000.00 - Php200,000.00 per month Benefits: - Paid training Work Location: Hybrid remote in Makati
Наблюдалась 2026-10-06, впервые 2026-09-24, источник — Indeed.