Junior AI Engineer: RAG & Agentic AI Solutions

ENCORA TECHNOLOGIES PTE. LTD.; Singapore; On-site; SGD 120,000 - 170,000; Full time

Job summary

ENCORA TECHNOLOGIES PTE. LTD. in Singapore is seeking an experienced ML/AI engineer to design and deploy production-ready AI solutions, including agents, RAG systems, and orchestration workflows.

You will collaborate across ML/DS, AI engineering, and data science to deliver scalable services. Responsibilities include building AI components, integrating with enterprise data sources, and applying MLOps practices for governance and observability.

Qualifications

• Hands-on experience building and deploying ML/AI solutions into production.
• Experience in Machine Learning Engineering, Data Science, AI Engineering, Advanced Analytics.
• Proficiency with Python and ML libraries (Scikit-Learn, XGBoost/LightGBM, TensorFlow or PyTorch).
• Experience with cloud and DevOps tools (Docker, Kubernetes, OpenShift, CI/CD, Git).

Responsibilities

• Design and develop AI agents using modern agent frameworks.
• Build and optimize RAG (Retrieval-Augmented Generation) solutions.
• Develop agent orchestration workflows and tool-calling frameworks.
• Implement prompt engineering, evaluation, reflection, and memory capabilities.
• Build reusable AI components for multiple business use cases.
• Develop machine learning models for client propensity, recommendations, classification and ranking, behavioral analytics, and next-best-action.

Skills

ML Engineering

Data Science

AI Engineering

Advanced Analytics

Tools

Python

SQL

REST APIs

Docker

Kubernetes

OpenShift

CI/CD

Git

Scikit-Learn

XGBoost

LightGBM

TensorFlow

PyTorch

RAG

Vector Search

LLM Apps

Dify

Agentic AI frameworks

Data Pipelines

Job description

ENCORA TECHNOLOGIES PTE. LTD. in Singapore is seeking an experienced ML/AI engineer to design and deploy production-ready AI solutions, including agents, RAG systems, and orchestration workflows.

You will collaborate across ML/DS, AI engineering, and data science to deliver scalable services. Responsibilities include building AI components, integrating with enterprise data sources, and applying MLOps practices for governance and observability.