AI Engineer (LLM/Prompt Engineer)

OPTIMUM SOLUTIONS (SINGAPORE) PTE LTD; Singapore; On-site; SGD 180,000 - 280,000; Full time

Job summary

OPTIMUM SOLUTIONS (SINGAPORE) PTE LTD is seeking an AI Engineer to design, develop, and deploy enterprise-grade AI and Generative AI solutions. You will build scalable AI pipelines, APIs, and production-ready ML systems in a large fintech environment in Singapore.

You will work with Python, PyTorch/TensorFlow, LangChain, LlamaIndex, and cloud platforms to implement RAG, AI agents, and governance practices across the lifecycle.

Qualifications

• 8+ years of software engineering experience, with at least 3 years focused on AI/ML engineering.
• Strong experience with Python and machine learning frameworks such as PyTorch, TensorFlow, or Scikit-learn.
• Hands-on experience with LLMs, prompt engineering, RAG, vector databases, and AI orchestration frameworks (e.g., LangChain or LlamaIndex).
• Experience deploying AI applications on cloud platforms such as AWS, Azure, or Google Cloud.
• Familiarity with MLOps, CI/CD pipelines, containerization (Docker/Kubernetes), and model deployment.
• Experience working with SQL, NoSQL, APIs, and modern data engineering practices.
• Strong understanding of AI security, governance, and responsible AI principles.

Responsibilities

• Design, develop, and deploy AI/ML and Generative AI applications for enterprise use cases.
• Build and maintain scalable AI pipelines, APIs, and production-ready machine learning solutions.
• Develop Retrieval-Augmented Generation (RAG), AI agents, and LLM-powered applications.
• Fine-tune, evaluate, and optimize large language models for performance, security, and cost efficiency.
• Collaborate with business stakeholders, product managers, and engineering teams to translate requirements into AI solutions.
• Integrate AI solutions with cloud platforms, enterprise systems, and data platforms.
• Implement AI governance, model monitoring, security, and responsible AI practices.

Skills

Python

AI/ML engineering

LLMs / Prompt engineering

MLOps

Cloud platforms (AWS/Azure/GCP)

SQL/NoSQL

Security & governance

Education

Bachelor's degree in Computer Science or related

Tools

PyTorch

TensorFlow

Scikit-learn

LangChain

LlamaIndex

Docker

Kubernetes

Vector databases

RAG

Job description

Our client is a leading global financial services organization undergoing large-scale digital transformation. They are looking for an AI Engineer to design, develop, and deploy enterprise-grade AI and Generative AI solutions that enhance business operations, improve customer experiences, and drive innovation across the organization.

Responsibilities

• Design, develop, and deploy AI/ML and Generative AI applications for enterprise use cases.
• Build and maintain scalable AI pipelines, APIs, and production-ready machine learning solutions.
• Develop Retrieval-Augmented Generation (RAG), AI agents, and LLM-powered applications.
• Fine-tune, evaluate, and optimize large language models (LLMs) for performance, security, and cost efficiency.
• Collaborate with business stakeholders, product managers, and engineering teams to translate business requirements into AI solutions.
• Integrate AI solutions with cloud platforms, enterprise systems, and data platforms.
• Implement AI governance, model monitoring, security, and responsible AI best practices.

Requirements

• 8+ years of software engineering experience, with at least 3 years focused on AI/ML engineering.
• Strong experience with Python and machine learning frameworks such as PyTorch, TensorFlow, or Scikit-learn.
• Hands-on experience with Large Language Models (LLMs), prompt engineering, RAG, vector databases, and AI orchestration frameworks (e.g., LangChain or LlamaIndex).
• Experience deploying AI applications on cloud platforms such as AWS, Azure, or Google Cloud.
• Bachelor's degree in Computer Science, Software Engineering, Artificial Intelligence, or a related discipline.
• Familiarity with MLOps, CI/CD pipelines, containerization (Docker/Kubernetes), and model deployment.
• Experience working with SQL, NoSQL, APIs, and modern data engineering practices.
• Strong understanding of AI security, governance, and responsible AI principles.