Microsoft Azure AI Engineer - Onsite (Taguig)

Quess Philippines Corp.; Philippines; On-site; PHP 1,200,000 - 2,000,000; Full time

Job summary

Quess Philippines Corp. is seeking an Azure AI Engineer to design, develop, and deploy AI solutions using Azure ML and Cognitive Services. You will build Python-based models, integrate prebuilt AI capabilities, and work with data engineers to translate business needs into AI-driven apps.

The role emphasizes responsible AI, data privacy, and governance, with opportunities to optimize performance, cost, and reliability across AI workloads in a scalable enterprise environment.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related field.
• 3+ years of experience designing and deploying AI/ML solutions on Azure.
• Proficiency in Python and Azure SDKs for ML and cognitive services.
• Strong understanding of AI/ML fundamentals: training, evaluation, deployment.
• Familiarity with CI/CD for ML workflows and cloud-native development.
• Excellent communication and collaboration skills.
• Experience with Azure ML Designer, AutoML, and Azure AI Studio.
• Knowledge of MLOps tools such as MLflow, Azure DevOps, or GitHub Actions.
• Microsoft certifications (Azure AI Engineer Associate) are a plus.
• Familiarity with Power BI for integrating AI insights into dashboards.

Responsibilities

• Design and implement AI solutions using Azure Machine Learning and Azure AI Services.
• Build and deploy Python-based ML models using Azure ML pipelines and SDKs.
• Integrate prebuilt AI capabilities (Vision, Language, Speech, Document Intelligence) into enterprise apps.
• Collaborate with data engineers, analysts, and stakeholders to translate requirements into AI solutions.
• Participate in solution architecture discussions to ensure enterprise standards and scalability.
• Apply Responsible AI principles ensuring fairness, transparency, and accountability.
• Ensure compliance with data privacy, security, and governance standards.
• Monitor AI workloads using Azure Monitor and Application Insights; adopt MLOps best practices.
• Continuously optimize model performance, cost-efficiency, and reliability.

Skills

Python

Azure SDKs

AI/ML fundamentals

CI/CD for ML workflows

Azure ML Designer

AutoML

MLflow

Azure DevOps

GitHub Actions

Power BI integration

Cloud-native development

Education

Bachelor's degree in Computer Science, Engineering, or a related field

Tools

Azure ML Studio

Azure AI Studio

Application Insights

Azure Monitor

Job description

About the role

A Microsoft Azure AI Engineer is responsible for designing, developing, and deploying intelligent solutions using Azure Machine Learning and Azure Cognitive Services. This role focuses on leveraging prebuilt AI capabilities and custom machine learning workflows to build scalable, secure, and responsible AI applications that meet business needs.

Key responsibilities

• Design and implement AI solutions using Azure Machine Learning, Azure AI Studio, and Azure AI Services.

• Build and deploy Python-based machine learning models using Azure ML pipelines and SDKs.

• Integrate prebuilt AI capabilities (Vision, Language, Speech, Document Intelligence) into enterprise applications.

• Work closely with data engineers, analysts, and business stakeholders to translate business requirements into AI-driven solutions.

• Participate in solution architecture discussions to ensure alignment with enterprise standards and scalability.

• Apply Responsible AI principles, ensuring fairness, transparency, and accountability in AI models.

• Ensure compliance with data privacy, security, and governance standards across AI workloads.

• Monitor AI workloads using Azure Monitor, Application Insights, and MLOps best practices.

• Continuously optimize model performance, cost-efficiency, and reliability.

About you

• Bachelor's degree in Computer Science, Engineering, or a related field.

• 3+ years of experience in designing and deploying AI/ML solutions on Azure.

• Proficiency in Python and Azure SDKs for machine learning and cognitive services.

• Strong understanding of AI/ML fundamentals, including model training, evaluation, and deployment.

• Familiarity with cloud-native development and CI/CD practices for ML workflows.

• Excellent communication and collaboration skills.

• Experience with Azure AI Studio, Azure ML Designer, and AutoML.

• Knowledge of MLOps practices and tools such as MLflow, Azure DevOps, or GitHub Actions.

• Microsoft certifications (e.g., Azure AI Engineer Associate) are a plus.

• Familiarity with Power BI for integrating AI insights into dashboards.