AI Engineer (Solution Design & Built)

Argyll Scott Singapore; Singapore; On-site; SGD 60,000 - 100,000; Full time

Job summary

Argyll Scott Singapore is seeking an AI Engineer to design, build, and deploy enterprise-grade AI and Generative AI solutions for a major financial services firm on a 12-month contract. You will collaborate with product, data, technology and platform teams to drive AI workflows from design to production deployment.

You will develop LLM-powered applications, RAG solutions and AI integrations, and participate in governance, testing, and deployment activities to ensure scalable, secure and

Qualifications

• Experience in AI, ML, Data Engineering or Software Engineering.
• Strong Python programming skills.
• Hands-on experience with Generative AI, LLMs, prompt engineering, and/or RAG solutions.
• Experience developing and deploying AI solutions.
• Understanding of LLM-powered applications, RAG, and AI workflows.
• Familiarity with cloud platforms such as Azure, AWS, or GCP.
• Understanding of software engineering best practices and APIs.
• Ability to work independently and drive delivery with minimal supervision.

Responsibilities

• Refine and complete existing solution design.
• Present designs during reviews and governance forums.
• Advise on cost-effective AI solutions versus existing STP solutions.
• Design, build and deploy enterprise-grade AI solutions.
• Develop LLM-powered applications, RAG solutions and AI workflows.
• Integrate AI solutions with enterprise systems and APIs.
• Support SIT and UAT.
• Assist CAB/release process and production deployment.
• Support production monitoring, optimization and troubleshooting.
• Collaborate with product, data, platform and technology teams.

Skills

Python

Generative AI

LLMs

RAG

AI/ML

Cloud platforms

APIs

Independence

Problem-solving

Job description

• Work with one of the large financial services firms - be a part of global projects
• 12 Months contract with a potential to extend on a long-term basis

Role Overview

The AI Engineer will be responsible for designing, building, and deploying enterprise-grade AI and Generative AI solutions, including LLM-powered applications, Retrieval-Augmented Generation (RAG) systems, and AI workflows.

The role will work closely with product, data, technology, and platform teams to take AI solutions from solution design through development, testing, governance, and production deployment.

Scope & Key Responsibilities

• Complete and refine the existing solution design.
• Participate in and present solution designs during reviews and governance forums, including GSRC, LSRC, etc.
• Support key decisions on where AI solutions would be cost-effective and appropriate versus existing Straight-Through Processing (STP) solutions.
• Design, build, and deploy enterprise-grade AI and Generative AI solutions.
• Develop LLM-powered applications, RAG solutions, and AI workflows, including agentic AI applications.
• Integrate AI solutions with enterprise systems and APIs.
• Support data and solution assessments to ensure the required data is available and suitable for the AI solution.li>
• Support System Integration Testing (SIT) and User Acceptance Testing (UAT).
• Support the CAB / release process and production deployment.
• Support production monitoring, optimisation, and troubleshooting.
• Collaborate with product, data, platform, and technology teams throughout the delivery lifecycle.

Requirements

• Experience in AI, Machine Learning, Data Engineering, or Software Engineering.
• Strong Python programming skills.
• Hands-on experience with Generative AI, LLMs, prompt engineering, and/or RAG solutions.
• Experience developing and deploying AI solutions.
• Understanding of LLM-powered applications, RAG, and AI workflows.
• Familiarity with cloud platforms such as Azure, AWS, or GCP.
• Understanding of software engineering best practices and APIs.
• Ability to work independently, take ownership, and drive delivery with minimal supervision.
• Strong problem-solving skills and a proactive, hands-on approach.

Preferred Skills

• Experience with vector databases.
• Experience with MLOps and/or LLMOps.
• Experience with agentic AI applications and workflows.
• Experience integrating AI solutions with enterprise systems and APIs.
• Experience working in enterprise or regulated environments.
• Exposure to technology governance, solution reviews, or production release processes.