AI Engineer

CLOUD KINETICS CONSULTING PTE. LTD.; Singapore; On-site; SGD 70,000 - 90,000; Full time

Job summary

A technology consulting firm in Singapore is seeking an experienced AI Engineer to develop and maintain AI/ML models. The role involves implementing MLOps, designing AI solutions, and ensuring compliance with security standards. Ideal candidates should have a strong background in both AWS and Azure platforms and possess experience in relevant industries such as Banking and Telecom. The position requires proficiency in Python, PySpark, and SQL, along with teamwork and communication skills.

Qualifications

• Minimum 2+ years of hands-on AI engineering experience.
• Must have deployed at least 2 GenAI/AI use cases to production.
• Domain/industry experience in Banking, Insurance, Manufacturing, and/or Telecom required.

Responsibilities

• Design and develop AI/ML foundation models and LLM-based solutions.
• Implement MLOps for AI operations including logging and monitoring.
• Ensure security compliance for all delivered AI models.
• Build data pipelines and semantic layers for AI model requirements.
• Analyze datasets for model building and training.
• Implement AI platforms on AWS and Azure.

Skills

Python

PySpark

LLMs

SQL

AWS

Azure AI

Data warehousing

Education

Bachelor's or Master's degree in AI-related fields combined with IT

Tools

Jupyter

Job description

Job Overview

We are seeking an experienced AI Engineer to join our Data & AI engineering team in Singapore. The ideal candidate will have a proven track record in hands‑on data engineering and AI/ML model development, testing, and deployment, particularly within the AWS Sagemaker and AWS Bedrock or Azure AI, and Azure OpenAI ecosystems. As an AI Engineer, you will be responsible for developing and maintaining MLOps frameworks and AI/ML models including LLMs, ensuring the reliability, accuracy, and scalability of AI solutions.

Responsibilities

1. Design and develop AI/ML foundation models and LLM-based solutions; fine‑tune custom models addressing specific industrial use cases using Agentic AI integrated with LLMs, SLMs, and ML workbenches.
2. Implement MLOps for AI operations including comprehensive logging and monitoring.
3. Ensure security compliance for all delivered AI models.
4. Build data pipelines and semantic layers for AI model requirements.
5. Analyze datasets and assess data feasibility for building, training, testing, and maintaining AI/ML models.
6. Implement AI platforms on AWS and Azure cloud environments.

Qualifications

• Bachelor's or Master's degree in AI‑related fields combined with IT.
• Minimum 2+ years of hands‑on AI engineering experience.
• Must have deployed at least 2 GenAI/AI use cases to production.
• Domain/industry experience in Banking, Insurance, Manufacturing, and/or Telecom required.

Primary Skills

• Proficient in Python, PySpark, LLMs, and SLMs.
• Proficient in SQL and data warehousing concepts.
• Proficient in Jupyter and other AI workbenches.
• Experience building AI/ML models.
• Proficient in AWS or Azure AI services.
• Understanding of data marts for presentation layers in reporting.
• Ability to build analytical output views for GenAI/AI implemented models.
• Strong communication skills with proficiency in English.