AI Architect

PRUDENTIAL ASSURANCE COMPANY SINGAPORE (PTE) LIMITED; Singapore; On-site; SGD 180,000 - 280,000; Full time

Job summary

PRUDENTIAL ASSURANCE COMPANY SINGAPORE (PTE) LIMITED seeks an AI Architect to bridge business strategy with AI technology, translating challenges into scalable AI, ML, and Generative AI solutions that deliver measurable outcomes.

You will engage senior leaders, advise on AI strategy, build business cases, and design end-to-end architectures using LangChain, RAG frameworks, MCP servers, and cloud platforms across Azure and GCP, while ensuring governance and enterprise standards.

Qualifications

• 5-7+ years in AI/ data/ solution architecture roles.
• Experience leading AI discovery and solution design with business stakeholders.
• Understanding of AI governance, security, and responsible AI.

Responsibilities

• Engage senior leaders to uncover opportunities and shape AI strategy.
• Design end-to-end AI/ML/Generative AI solution architectures that are scalable and secure.
• Define architecture patterns, reference designs, and reusable AI capabilities for enterprise-wide adoption.
• Lead solution design for Agentic AI, RAG, and AI orchestration frameworks.

Skills

AI architectures

Generative AI

LLMs

NLP

MLOps

observability

data architecture

APIs

Education

Bachelor's or Master’s in CS/DS/Engineering/IT

Tools

LangChain

LangGraph

RAG frameworks

MCP servers

Model APIs

AI orchestration platforms

Databricks

MLFlow

Job description

As an AI Architect, you will serve as the bridge between business strategy and AI technology, helping business stakeholders identify, shape, and prioritize AI opportunities that deliver measurable outcomes. You will partner closely with business leaders, product owners, and technology teams to translate business challenges into scalable AI, Machine Learning, and Generative AI solutions.

Role Duties & Responsibilities:

• Engaging senior business leaders to uncover opportunities.

• Advising stakeholders on AI strategy and adoption.

• Building business cases and demonstrating value realization.

• Responsible for solution envisioning, architecture design, and adoption strategy

• Design end-to-end AI, ML, and Generative AI solution architectures that are scalable, secure, and aligned with enterprise standards.

• Define architecture patterns, reference designs, and reusable AI capabilities for enterprise-wide adoption.

• Lead solution design for emerging AI technologies including Agentic AI, RAG architectures, MCP servers, Model APIs, and AI orchestration frameworks.

• Define best practices for AI solution deployment, MLOps, LLMOps, monitoring, and lifecycle management.

• Drive standardization of AI design patterns, architecture principles, and development methodologies.

Competencies & Personal Traits

• Strong understanding of AI, Machine Learning, Generative AI, Large Language Models (LLMs), NLP, and Agentic AI frameworks.

• Experience designing AI solution architectures using technologies such as LangChain, LangGraph, RAG frameworks, MCP servers, and AI orchestration platforms.

• Knowledge of cloud-based AI platforms across Azure and GCP

• Understanding of MLOps, LLMOps, model governance, observability, and responsible AI practices.

• Familiarity with data architecture, integration patterns, APIs, and scalable enterprise platforms.

• Experience developing reusable services and AI enablement capabilities is advantageous.

• Experience with Databricks, MLFlow, and modern AI/ML ecosystems is a plus.

Working Experience

• 5-7+ years of experience in AI, data, solution architecture, or enterprise architecture roles.

• Proven experience leading AI discovery, solution design, and architecture engagements with business stakeholders.

• Experience designing and delivering enterprise AI and Generative AI solutions from concept through implementation.

• Strong understanding of AI governance, security, compliance, and responsible AI principles.

• Experience within insurance, financial services, or highly regulated industries is advantageous.

• Master/Bachelor's degree in Computer Science, Data Science, Engineering, Information Technology, or a related discipline.