AI Engineer

AVENSYS CONSULTING INC.; Makati; Hybrid; PHP 1,200,000 - 1,800,000; Full time

Job summary

AVENSYS CONSULTING INC. in Makati City, Philippines is seeking an AI Engineer to join our hybrid team. You will develop and deploy AI/ML solutions across enterprise data platforms, focusing on generative AI, ML lifecycle, and scalable pipelines.

You will work with Azure AI services, Databricks, and MLOps practices to build production-ready models, integrate with data lakehouse architectures, and deliver reliable AI capabilities for our clients.

Qualifications

• Experience in building and deploying AI/ML models.
• Proficiency with Python/SQL for data processing.
• Familiar with MLOps, CI/CD for ML workflows.
• Ability to design scalable AI solutions for enterprise data.

Responsibilities

• Design, build, and deploy AI/ML solutions for enterprise data products.
• Develop predictive analytics, anomaly detection, and automation use cases.
• Implement Generative AI using LLMs, RAG, and prompting techniques.
• Collaborate with data engineers to embed AI in data pipelines and lakehouse architectures.

Skills

AI & ML Engineering

Cloud AI & Data Platforms

Data Engineering & Integration

MLOps & Deployment

Tools

Azure AI services

Microsoft Fabric AI

Databricks

Azure DevOps

Git-based source control

Job description

Job Description

Avensys is a reputed global IT professional services company headquartered in Singapore. Our service spectrum includes enterprise solution consulting, business intelligence, business process automation and managed services. Given our decade of success, we have evolved to become one of the top trusted providers in Singapore and service a client base across banking and financial services, insurance, information technology, healthcare, retail and supply chain.

We are currently looking for AI Engineer who has proven track record in IT Industry. This is an exciting opportunity to expand your skill set, achieve job satisfaction and work-life balance. More details as below.

Job Details

• Role: AI Engineer
• Employment Type: Permanent Role
• Notice Period: Immediate Joiners/ 1 months
• Work Mode: Hybrid (2 days work from office)
• Work Location: Makati City, Philippines

Mandatory skills

AI & Machine Learning Engineering, Cloud AI & Data Platforms, Data Engineering & Integration, MLOps & Deployment.

Job Summary

AI & Machine Learning Engineering

• Machine learning model development and lifecycle management

• Feature engineering, model training, evaluation, and deployment

• Familiarity with supervised and unsupervised learning techniques

• Experience with model serving and inference pipelines

Cloud AI & Data Platforms

• Azure AI services (Azure Machine Learning, Cognitive Services, OpenAI integration)

• Microsoft Fabric AI capabilities (Copilot, AutoML, intelligent insights)

• Databricks (MLflow, Model Registry, Delta Lake)

• Understanding of Lakehouse architecture and AI integration patterns

Data Engineering & Integration

• Strong Python and/or SQL for data processing and model integration

• Experience with data pipelines and orchestration tools

• Knowledge of data transformation and feature pipelines

• Integration of AI outputs into downstream analytics systems

MLOps & Deployment

• CI/CD pipelines for machine learning models

• Model versioning, monitoring, and retraining strategies

• Logging, observability, and performance tuning of AI solutions

Delivery & Tooling

• Azure DevOps (ADO) for backlog and work tracking

• Git-based source control for code and model artifacts

Overview of Work

Design, build, and deploy AI/ML solutions that integrate with enterprise data products, pipelines, and lakehouse architectures.

Develop and operationalize machine learning models and AI services for use cases such as predictive analytics, anomaly detection, and automation.

Design and implement Generative AI solutions using LLMs, including RAG architecture and prompt engineering.

Collaborate with data engineers to embed AI capabilities into data pipelines and ensure seamless integration with data platforms (e.g., Fabric, Databricks).