Data Integration Specialist ( AI Engineer )

The HIRD- Philippines; Manila; On-site; PHP 600,000 - 1,200,000; Full time

Job summary

The HIRD- Philippines is seeking an AI Engineer to join an enterprise Data & AI team, building production-ready AI/ML and Generative AI solutions integrated with modern data platforms in the Philippines.

You will design, deploy and monitor AI systems across Azure/Microsoft Fabric/Databricks, implement MLOps, and collaborate with data engineers, product owners and stakeholders to scale AI in production.

Qualifications

• Strong Python and/or SQL skills.
• Hands-on experience in Machine Learning / AI Engineering.
• Experience with model development, evaluation and deployment.
• Experience with Generative AI, LLMs, RAG and Prompt Engineering.
• Experience with Databricks / MLflow / Model Registry is highly desirable.
• Exposure to Microsoft Fabric and Lakehouse architectures is a plus.
• Knowledge of data pipelines, feature engineering and orchestration.
• Understanding of MLOps, CI/CD, Git and model monitoring.
• Experience working in Agile enterprise environments.

Responsibilities

• Design, develop and deploy AI/ML solutions for enterprise data products.
• Build Generative AI / LLM solutions, including RAG and prompt engineering.
• Develop solutions for predictive analytics, anomaly detection and automation.
• Integrate AI/ML capabilities into data pipelines and lakehouse platforms.
• Build and manage model training, deployment, inference and monitoring workflows.
• Work with Azure, Microsoft Fabric and/or Databricks environments.
• Implement MLOps practices including model versioning, CI/CD, monitoring and retraining.
• Partner with Data Engineers, Architects, Product Owners and business stakeholders.
• Ensure AI solutions are scalable, reliable, explainable and production-ready.
• Follow enterprise AI governance and Responsible AI practices.

Skills

Python

SQL

Machine Learning

AI Engineering

Generative AI

LLMs

RAG

Prompt Engineering

Databricks

MLflow

Model Registry

Microsoft Fabric

Azure

Data Pipelines

Feature Engineering

MLOps

CI/CD

Git

Tools

Databricks

MLflow

Model Registry

Microsoft Fabric

Azure

Git

Job description

We are looking for an AI Engineer to join an enterprise Data & AI team and help build production-ready AI/ML and Generative AI solutions integrated with modern data platforms.

This is a great opportunity for someone who enjoys working across AI, Machine Learning, Data Engineering, and Cloud technologies and wants to work on enterprise-scale use cases.

What You'll Do

• Design, develop and deploy AI/ML solutions for enterprise data products
• Build Generative AI / LLM solutions, including RAG and prompt engineering
• Develop solutions for predictive analytics, anomaly detection and automation
• Integrate AI/ML capabilities into data pipelines and lakehouse platforms
• Build and manage model training, deployment, inference and monitoring workflows
• Work with Azure, Microsoft Fabric and/or Databricks environments
• Implement MLOps practices including model versioning, CI/CD, monitoring and retraining
• Partner with Data Engineers, Architects, Product Owners and business stakeholders
• Ensure AI solutions are scalable, reliable, explainable and production-ready
• Follow enterprise AI governance and Responsible AI practices

What We’re Looking For

• Strong Python and/or SQL skills
• Hands-on experience in Machine Learning / AI Engineering
• Experience with model development, evaluation and deployment
• Experience with Generative AI, LLMs, RAG and Prompt Engineering
• Experience with Databricks / MLflow / Model Registry is highly desirable
• Exposure to Microsoft Fabric and Lakehouse architectures is a plus
• Knowledge of data pipelines, feature engineering and orchestration
• Understanding of MLOps, CI/CD, Git and model monitoring
• Experience working in Agile enterprise environments

Nice to Have

• Data governance and data quality knowledge
• Experience integrating AI into enterprise workflows

We're looking for an engineer who can go beyond building models — someone who can take AI from experimentation to production and integrate it into real enterprise data products and business processes.