AI Engineer

PeoplePlusTech Inc.; Metro Manila; On-site; PHP 1,000,000 - 2,000,000; Full time

Job summary

PeoplePlusTech Inc. in the Philippines seeks an experienced AI Engineer to design, develop, and deploy AI-driven solutions that enhance business processes, automation, analytics, and decision-making.

The role collaborates with data engineering, analytics, architecture, and product teams to build scalable, production-ready AI solutions while ensuring governance and Responsible AI standards. Responsibilities include deploying ML models, integrating AI into data pipelines and dashboards, and

Qualifications

• Experience developing and deploying machine learning models.
• Strong feature engineering, model training, evaluation, and deployment.
• Knowledge of supervised and unsupervised learning techniques.
• Experience with model serving and inference pipelines.

Responsibilities

• Design, develop, and deploy AI/ML solutions integrated with enterprise data platforms and business applications.
• Build and operationalize ML models for predictive analytics, anomaly detection, forecasting, and automation.
• Develop Generative AI solutions leveraging LLMs, Retrieval-Augmented Generation (RAG), and prompt engineering techniques.
• Integrate AI capabilities into existing data pipelines, lakehouse architectures, and cloud platforms.
• Collaborate with stakeholders to translate business requirements into scalable AI solutions.
• Implement model monitoring, logging, performance optimization, and lifecycle management processes.
• Support deployment and integration of AI outputs into dashboards, reports, and operational workflows.
• Ensure AI solutions align with governance, compliance, and Responsible AI principles.
• Maintain technical documentation, model artifacts, and knowledge repositories.
• Participate in Agile ceremonies and continuous improvement initiatives.

Skills

Machine learning

Generative AI

Python development

SQL development

MLOps

DevOps

Tools

LLMs

RAG

Prompt engineering

Azure AI services

Azure ML

Cognitive Services

OpenAI integrations

Databricks

MLflow

Python

SQL

Data pipelines

Job description

We are seeking an experienced AI Engineer to design, develop, and deploy AI-driven solutions that enhance business processes, automation, analytics, and decision-making capabilities. The ideal candidate will have experience in machine learning, Generative AI, enterprise data platforms, and cloud-based AI technologies.

This role will collaborate closely with data engineering, analytics, architecture, and product teams to build scalable, production-ready AI solutions while ensuring compliance with governance and Responsible AI standards.

Responsibilities

• Design, develop, and deploy AI/ML solutions integrated with enterprise data platforms and business applications.
• Build and operationalize machine learning models for predictive analytics, anomaly detection, forecasting, and automation.
• Develop Generative AI solutions leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and prompt engineering techniques.
• Integrate AI capabilities into existing data pipelines, lakehouse architectures, and cloud platforms.
• Collaborate with stakeholders to translate business requirements into scalable AI solutions.
• Implement model monitoring, logging, performance optimization, and lifecycle management processes.
• Support deployment and integration of AI outputs into dashboards, reports, and operational workflows.
• Ensure AI solutions align with governance, compliance, and Responsible AI principles.
• Maintain technical documentation, model artifacts, and knowledge repositories.
• Participate in Agile ceremonies and continuous improvement initiatives.

Requirements

• Experience developing and deploying machine learning models.
• Strong understanding of feature engineering, model training, evaluation, and deployment.
• Knowledge of supervised and unsupervised learning techniques.
• Experience with model serving and inference pipelines.

Generative AI

• Hands-on experience with LLMs, prompt engineering, and RAG architectures.
• Experience integrating AI services into enterprise applications.
• Experience with Azure AI services, Azure Machine Learning, Cognitive Services, or OpenAI integrations.
• Experience with Microsoft Fabric, Databricks, MLflow, or similar AI platforms.
• Understanding of lakehouse and modern data architectures.
• Strong Python and SQL development skills.
• Experience building and maintaining data pipelines and feature stores.
• Knowledge of data integration and transformation frameworks.

MLOps & DevOps

• Experience with CI/CD pipelines for AI and ML deployments.
• Knowledge of model monitoring, versioning, and retraining strategies.
• Experience using Git and Azure DevOps.

Preferred Qualifications

• Experience with enterprise analytics platforms.
• Familiarity with IT operational data and Service Management platforms.
• Knowledge of data governance and data quality practices.
• Understanding of Responsible AI principles and governance frameworks.