Manager Azure AI Engineer

Key Responsibilities

• AI Solution Design & Development
• Build, train, and deploy machine learning models using Azure Machine Learning, Python, Azure AI Foundry and Azure ML SDKs.
• Develop scalable AI pipelines using Azure ML pipelines, AutoML, and cloud-native best practices.
• Integrate Azure AI capabilities—Vision, Language, Speech, and Document Intelligence—into enterprise applications.
• Design and automate AI-driven solutions using the Power Platform (Power Apps, Power Automate, Power Virtual Agents) integrated with Azure AI Services.
• Utilize Azure AI Studio, Azure AI Foundry to rapidly prototype and deliver generative AI, agentic AI and cognitive solutions.

 Cross-Functional Collaboration

• Partner with data engineers, analytics teams, and business stakeholders to translate business needs into impactful AI solutions.
• Collaborate with Power Platform developers to embed AI models and cognitive services into low-code applications and workflows.
• Contribute to architecture decisions ensuring scalability, maintainability, and alignment with enterprise cloud standards.
• Communicate technical concepts clearly to both technical and non-technical audiences.

 Responsible AI, Security & Governance

• Apply Responsible AI guidelines, ensuring fairness, explainability, and ethical use of machine learning models.
• Enforce data privacy, compliance, and security standards across all AI workloads.
• Support model versioning, governance, and lifecycle management.

 MLOps, Monitoring & Optimization

• Implement monitoring and observability for AI workloads using Azure Monitor, Application Insights, and MLflow (where applicable).
• Optimize model performance, reliability, and cost efficiency across training and inference workloads.
• Contribute to CI/CD workflows for ML and Power Platform integrations using Azure DevOps or GitHub Actions.

For This Role, You Will Need:

• Bachelor’s degree in computer science, Computer Engineering, IT, or related discipline.
• Hands-on experience designing and deploying AI/ML solutions on Microsoft Azure.
• Experience with Azure AI Studio, Azure AI Foundry, Azure ML Designer, AutoML, and Prompt engineering Flow.
• Strong proficiency in Python and Azure SDKs for ML and Cognitive Services.
• Solid understanding of machine learning concepts: data preparation, model development, evaluation, and deployment.
• Experience with cloud-native development and CI/CD for ML pipelines.
• Strong communication, collaboration, and problem-solving skills.

Preferred Qualifications That Set You Apart:

• Exposure to Microsoft Power Platform and integrating Azure AI models/services into Power Apps, Power Automate, and Copilots.
• Familiarity with MLOps practices and tools such as MLflow, Azure DevOps, or GitHub Actions.
• Microsoft certifications (e.g., Azure AI Engineer Associate, Azure Data Scientist Associate) are an added advantage.
  • Working knowledge of Power BI for embedding or visualizing AI-driven insights.