Azure AI Engineer
Job Location:
Manila - Philippines
Monthly Salary:
Posted:
Application Deadline:
Vacancies:
Job Summary
The AI Engineer designs builds deploys and maintains AI models and systems that enable scalable
business solutions. Leveraging cloud platforms such as Microsoft Azure the role develops
production-ready AI pipelines and integrates intelligent capabilities into enterprise applications.
Working closely with Data Engineers Software Engineers and Product Teams the AI Engineer ensures
eļ¬cient data flow reliable model deployment and continuous performance optimization. The role is
responsible for improving model accuracy scalability and reliability in real-world environments.
The AI Engineer also upholds best practices in data quality security governance and Responsible AI
ensuring solutions are ethical compliant and aligned with organizational and regulatory standards.
Job Description:
Design build and deploy AI models and end-to-end AI pipelines for production environments
Integrate AI capabilities into applications and services using APIs and cloud-native architectures
Collaborate with Data Engineers Software Engineers and Product Teams to ensure seamless
data flow and system integration
Monitor evaluate and optimize model performance accuracy and scalability in real-world use
Develop and manage Prompt Flows orchestration pipelines and agent-based AI workflows
Implement Retrieval-Augmented Generation (RAG) solutions including embedding indexing
and context management
Ensure adherence to Responsible AI practices including model safety governance and
compliance standards
Establish observability logging and performance monitoring for AI systems
Apply secure-by-design principles including identity management access control and data
protection
Translate business requirements into AI solutions defining guardrails KPIs and success criteria.
Requirements:
Related Work Experience - 36 years in AI/ML software engineering or cloud-based AI
solution development
a. Hands-on experience building and deploying AI/LLM-powered applications in
production
b. Experience with Azure or similar cloud platforms (AWS/GCP)
c. Proven work on prompt engineering orchestration or RAG-based solutions
d. Experience collaborating in cross-functional product or engineering teams
Knowledge knowledgeable in the following:
a. AI/LLM engineering: prompt design orchestration (Prompt Flow) agent-based systems
and RAG implementation
b. c. Software engineering: Python APIs (REST/JSON) microservices and CI/CD practices
Azure AI ecosystem: AI Foundry model deployment inference APIs and cost
Required Skills:
Design build and deploy AI models and end-to-end AI pipelines for production environments Integrate AI capabilities into applications and services using APIs and cloud-native architectures Collaborate with Data Engineers Software Engineers and Product Teams to ensure seamless data flow and system integration Monitor evaluate and optimize model performance accuracy and scalability in real-world use Develop and manage Prompt Flows orchestration pipelines and agent-based AI workflows
Required Education:
Design build and deploy AI models and end-to-end AI pipelines for production environmentsIntegrate AI capabilities into applications and services using APIs and cloud-native architecturesCollaborate with Data Engineers Software Engineers and Product Teams to ensure seamlessdata flow and system integrationMonitor evaluate and optimize model performance accuracy and scalability in real-world use
