AI Solutions Architect

Eames Consulting; Singapore; On-site; SGD 180,000 - 260,000; Full time

Job summary

Eames Consulting, on behalf of a global financial institution, seeks a seasoned Solution Architect to lead the design and integration of an enterprise AI platform across the region.

You will bridge strategic business objectives with production‑ready AI deployments, ensuring architectures are secure, scalable, and governed.

Candidates should have 8+ years in software engineering and data architecture, cloud experience (AWS/Azure/GCP), and hands‑on Python/Java/Scala.

Qualifications

• 8+ years in software engineering, data architecture, and distributed systems.
• 5+ years designing production AI/ML solutions.
• Experience with secure SDLC, model monitoring, and regulatory standards.
• Bachelor’s or Master’s in CS/AI/Data Engineering or related field.

Responsibilities

• Architect end-to-end blueprint for an enterprise AI platform including data pipelines and deployment infra.
• Translate complex use cases into modular, scalable technical roadmaps and microservices.
• Collaborate with engineering, data science, and executives to deploy ML and generative AI solutions.
• Define governance, data privacy boundaries, and security guardrails for AI systems.
• Ensure architectures meet high-availability, scalability, and regulatory performance standards.

Skills

Cloud architecture

Microservices

API-first design

Python

Java

Scala

Data engineering

Regulatory compliance

Education

Bachelor's or Master’s in CS/AI/Data Engineering

Tools

AWS

Azure

GCP

Python

Java

Scala

Job description

We are partnered with an established global financial institution looking to expand their enterprise technology capabilities across the region.

They are seeking a seasoned Solution Architect spearhead the design and integration of their core enterprise AI platform. In this role, you will be the bridge between strategic business objectives and enterprise-grade AI deployment, ensuring architectures are production-ready, highly secure, and optimised for scale.

Key Responsibilities:

• Architect and lead the end-to-end blueprint for an enterprise level AI platform, covering data pipelines, deployment infrastructure, and live model lifecycle management.
• Convert complex institutional use cases into modular, scalable technical roadmaps and microservices architectures.
• Partner with cross-functional engineering teams, data science units, and executive stakeholders to drive the execution of modern machine learning and generative AI solutions.
• Define and enforce governance frameworks, data privacy boundaries, and enterprise security guardrails across all deployed AI systems.
• Ensure all deployed architectures adhere strictly to high-availability, scalability, and regulated platform performance standards.

Requirements:

• At least 8 years of experience in software engineering, data architecture, and distributed systems, with 5+ years dedicated specifically to production AI/ML solution design.
• Strong architectural proficiency across major cloud environments (AWS, Azure, or GCP) utilizing modern microservices and API-first designs.
• Hands-on familiarity with core programming environments (Python, Java, or Scala), data engineering frameworks, and generative AI/LLM deployment patterns.
• Deep knowledge of secure SDLC, model monitoring, and regulatory compliance standards within heavily governed domains (e.g., Banking, Financial Services, Healthcare).
• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Engineering, or a related technical discipline.