Artificial Intelligence Architect

UST; Kampung Malaysia Tambahan; On-site; MYR 250,000 - 500,000; Full time

Job summary

UST seeks an experienced AI-SDLC Architect (FDE) in Malaysia to transform traditional software lifecycles into AI-native, agentic workflows. Lead architecture, CI/CD, and governance for enterprise-scale AI-enabled delivery.

Role requires hands-on expertise with AI tools, spec-driven development, Terraform IaC, and cloud platforms. You will guide clients, perform design reviews, and foster secure, scalable AI-enabled software delivery.

Qualifications

• 12-15 years of software engineering, architecture, or platform engineering.
• Hands-on with AI development tools (Copilot, Claude Code, VS Code AI).
• Experience with spec-driven development (SpecKit/OpenSpec/BMD).
• Knowledge of AI artifact management and AI guardrails.
• Experience in agent memory management and multi-agent orchestration.
• Experience architecting AI-native delivery platforms for enterprises.
• Strong knowledge of FastAPI or similar API frameworks.
• Experience with Azure OpenAI, AWS Bedrock or similar AI gateways.
• IaC and CI/CD using Terraform and GitHub Actions.

Responsibilities

• Architect and implement AI-native SDLC workflows from spec to deployment.
• Design AI coding agent architectures integrated with pipelines and cloud platforms.
• Define reference architectures, blueprints, and governance models for AI delivery.
• Build scalable, secure CI/CD pipelines with AI tooling and gates.
• Collaborate with client engineering teams to drive adoption of agentic practices.
• Provide technical leadership, design reviews, and best practices for AI-enabled software engineering.

Skills

AI-native SDLC

Spec-driven development

AI governance

AI artifact management

Multi-agent orchestration

Enterprise delivery platforms

FastAPI knowledge

Cloud platforms

CI/CD best practices

Tools

GitHub Copilot

Copilot CLI

Claude Code

VS Code AI extensions

Terraform

GitHub Actions

Job description

We are seeking an experienced AI-SDLC Architect (FDE) to help enterprise engineering teams transform traditional software development lifecycles into AI-native, agentic development workflows. The ideal candidate will combine expertise in AI-powered software engineering, platform architecture, CI/CD, and stakeholder engagement to drive AI-assisted development at scale.

Key Responsibilities

• Architect and implement AI-native SDLC workflows, from specification-driven development through deployment.
• Design and deploy AI coding agent architectures integrated with enterprise development pipelines and cloud platforms.
• Define reference architectures, blueprints, and governance models for AI-assisted software delivery.
• Build scalable, secure CI/CD pipelines incorporating AI tooling, security controls, and quality gates.
• Collaborate directly with client engineering teams to drive adoption of agentic development practices.
• Provide technical leadership, design reviews, and best practices for AI-enabled software engineering.

Mandatory Requirements

• 12-15 years of experience in software engineering, architecture, or platform engineering.
• Hands-on experience with AI development tools such as GitHub Copilot, Copilot CLI, Claude Code, VS Code AI extensions, or equivalent.
• Experience implementing spec-driven development using SpecKit, OpenSpec, BMD, or similar frameworks.
• Strong understanding of AI artifact management, FinOps/token consumption management, and AI guardrails.
• Experience designing agent memory management (static, dynamic, and episodic memory) and multi-agent orchestration.
• Proven expertise in architecting AI-native software delivery platforms and developer workflows for enterprise environments.
• Strong knowledge of FastAPI (or equivalent API frameworks).
• Experience with Azure OpenAI, Amazon Bedrock, or similar AI gateway architectures.
• Expertise in Infrastructure as Code (Terraform) and CI/CD pipelines using GitHub Actions or equivalent tools.

Preferred Skills

• Experience as a Forward Deployed Engineer, Solution Architect, or Lead Engineer working directly with client teams.
• Experience with AI security, evaluation frameworks, observability, and monitoring.
• Knowledge of Docker, Kubernetes, cloud-native deployments, and enterprise security practices.
• Exposure to both AWS and Azure environments.