Microsoft Azure AI Engineer

Job Overview

We are looking for a skilled Microsoft Azure AI Engineer to design, develop, and deploy intelligent AI/ML solutions using Microsoft Azure. The role focuses on building scalable, secure, and responsible AI applications using Azure Machine Learning, Azure AI Studio, and Azure AI Services.

The ideal candidate should have strong hands-on experience in AI/ML, Microsoft Azure, Python, Azure Machine Learning, Azure AI Services, model development and deployment, along with a good understanding of MLOps, cloud-native development, and responsible AI practices.

Key Responsibilities
AI Solution Development

• Design, develop, and deploy AI/ML 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 Azure AI capabilities such as Vision, Language, Speech, and Document Intelligence into enterprise applications.

• Develop scalable and reliable AI solutions aligned with business requirements.

• Support model training, evaluation, deployment, and optimization.

Collaboration & Business Alignment

• Work closely with data engineers, data analysts, developers, and business stakeholders.

• Translate business requirements into practical AI/ML solutions.

• Participate in solution architecture and technical design discussions.

• Ensure AI solutions align with enterprise architecture, scalability, security, and development standards.

• Collaborate with cross-functional teams throughout the AI solution lifecycle.

Responsible AI & Governance

• Apply Responsible AI principles throughout AI/ML development and deployment.

• Promote fairness, transparency, accountability, and responsible use of AI models.

• Ensure AI workloads follow applicable data privacy, security, and governance requirements.

• Support secure and compliant implementation of AI solutions.

Monitoring & Optimization

• Monitor deployed AI/ML workloads using Azure Monitor and Application Insights.

• Identify and troubleshoot performance, reliability, and deployment issues.

• Optimize model performance, resource utilization, cost efficiency, and reliability.

• Apply MLOps best practices to improve the lifecycle management of machine learning solutions.

Required Qualifications & Experience

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

• Minimum 3 years of professional experience in AI/ML.

• Hands-on experience designing and deploying AI/ML solutions on Microsoft Azure.

• Strong proficiency in Python.

• Experience with Azure SDKs and machine learning services.

• Strong understanding of AI/ML fundamentals, including:

  • Model training

  • Model evaluation

  • Model deployment

  • Machine learning workflows

• Experience with Azure Machine Learning.

• Understanding of cloud-native application development.

• Familiarity with CI/CD practices for ML workflows.

• Strong communication, analytical, and collaboration skills.

Preferred Skills

• Experience with Azure AI Studio.

• Experience with Azure ML Designer.

• Experience with Azure AutoML.

• Knowledge of MLOps practices.

• Experience with MLflow.

• Experience with Azure DevOps.

• Experience with GitHub Actions.

• Microsoft Azure AI certifications, such as Azure AI Engineer Associate, are a plus.

• Familiarity with Power BI for integrating AI-generated insights into dashboards and business reporting.

Technical Skills

Mandatory / Core Skills:

• Microsoft Azure

• Azure Machine Learning

• Azure AI Services

• Azure AI Studio

• Python

• AI/ML

• Machine Learning Models

• Model Training & Evaluation

• Model Deployment

• Azure ML Pipelines

• Azure ML SDKs

• Cloud-Native Development

• Responsible AI

• AI Governance

Additional Skills:

• Azure Monitor

• Application Insights

• MLOps

• MLflow

• Azure DevOps

• GitHub Actions

• Azure ML Designer

• AutoML

• Power BI

• CI/CD

• Data Privacy & Security

Soft Skills

• Strong analytical and problem-solving skills.

• Excellent communication and interpersonal skills.

• Ability to work effectively with technical and business stakeholders.

• Strong collaboration and teamwork capabilities.

• Ability to understand business requirements and translate them into technical solutions.

• Strong attention to detail.

• Ability to manage multiple priorities in a fast-paced environment.

• Proactive approach to troubleshooting and continuous improvement.

Work Setup & Eligibility

• Work Mode: Onsite

• Location: Taguig, Philippines

• Shift: Shifting

• Candidates must currently be located in the Philippines.

• Candidates must already have the legal right to live and work in the Philippines.

• Candidates must be willing to work onsite in Taguig.

• Candidates must be flexible to work in shifting schedules.

Recruitment Process

The recruitment process may include:

1. Initial screening with CV Reviewer.

2. Candidate endorsement for validation.

3. Further CV screening through Workday along with the required HRI toolkit, FCV, and updated CV.

4. Client review and selection.

Pre-Screening Questions

1. How many years of professional experience do you have in AI/ML?

2. How many years of hands-on experience do you have designing or deploying AI/ML solutions on Microsoft Azure?

3. How would you rate your understanding of AI/ML fundamentals, including model training, evaluation, and deployment?

4. What was your last drawn salary?

5. What is your salary expectation?

6. Are you amenable to working onsite in Taguig with a shifting schedule?

7. What is your notice period?