Lead Architect (AI, Cloud & Azure)

Job description

Description and Requirements Lead Architect Location

Kuala Lumpur (KL), Malaysia Department: Global Technology – Architecture (Asia) Role Value Proposition The Lead Architect is responsible for defining, governing, and scaling enterprise and domain architectures across Artificial Intelligence (AI), Generative AI (GenAI), Agentic AI, Identity and Access Management (IAM), Customer Identity and Access Management (CIAM), Cloud & Infrastructure. The role ensures MetLife’s platforms are secure, resilient, scalable, and compliant, while accelerating cloud‑first and AI‑driven digital transformation across Asia.

Key Responsibilities

AI, GenAI & Agentic AI Architecture Define enterprise architecture for AI, GenAI, and Agentic AI platforms including model lifecycle management, orchestration, tooling, and integration with enterprise platforms. Architect Large Language Model (LLM) based solutions using commercial and open‑source models, applying retrieval‑augmented generation (RAG), fine‑tuning, prompt engineering, and agent‑based patterns Establish standards and reference architectures for ML and GenAI tooling such as feature stores, vector databases, model registries, MLOps / LLMOps pipelines, and AI observability frameworks.

Ensure responsible AI, explainability, data privacy, bias mitigation, and regulatory compliance are embedded by design. IAM & CIAM Architecture Own workforce IAM and CIAM architecture including authentication, authorization, federation, consent management, and digital identity lifecycle. Drive zero‑trust, least‑privilege, and privacy‑by‑design identity solutions. Cloud & Azure Architecture Provide architectural leadership for Microsoft Azure including landing zones, identity integration, governance, networking, security, resilience, and cost controls.

Define hybrid and multi‑cloud reference architectures aligned to enterprise and regulatory standards. Infrastructure & Reliability Engineering Lead infrastructure architecture for availability, disaster recovery, performance, observability, and resilience across cloud and on‑prem platforms. Promote SRE, automation‑first, and reliability engineering practices. Architecture Governance & Risk Management Serve as a contributor to Architecture Review Boards and AI governance forums, enforcing enterprise architecture, security, and AI risk standards.

Identify architectural risks and communicate technology trade‑offs to senior stakeholders.

Skills & Competencies

• Deep expertise in Microsoft Azure architecture and cloud platforms
• Strong hands‑on knowledge of AI, GenAI, Agentic AI, LLMs, and ML platforms
• Experience with ML tools, frameworks, and AI orchestration patterns
• IAM and CIAM security‑by‑design principles
• Executive communication, influence, and decision‑making

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field
• 10+ years of progressive IT and architecture experience

Microsoft Certified

• Azure Solutions Architect Expert (preferred)
• Microsoft Azure AI Engineer Associate or Azure AI certification (preferred)
• Architecture, cloud, security, or identity certifications preferred