- Kuala Lumpur Federal Territory Malaysia
Happiest Minds Technologies Hiring! Full Time SOLUTIONS ARCHITECT - Architecture - Technology Management in Federal Territory - Ricebowl
SOLUTIONS ARCHITECT - Architecture - Technology Management
Happiest Minds Technologies
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Job Description ? Underwriting AI Solution Architect (Life and Health) or Underwriting AI Technical Prompt Engineer (Life and Health)
Location: Kuala Lumpur, Malaysia
Role Type: Individual Contributor
Domain: Life & Health Underwriting Transformation (AI & Agentic Systems)
Role Purpose
This role is responsible for designing, developing, and optimising prompt frameworks and AI-driven decision-support capabilities within the AI-enabled New Business Underwriting (NB UW) program.
The role sits at the intersection of Life & Health underwriting expertise and Generative AI, ensuring that AI outputs are clinically sound, risk-aligned, explainable, and regulator-ready. The individual will translate using internal underwriting manuals, reinsurance (RI) guidelines, and decision rules into structured prompts and AI workflows, enabling scalable, consistent, and high-quality underwriting outcomes across markets.
Key Responsibilities
Translation of UW Knowledge into AI Logic
Codify Underwriting Expertise Into Structured Logic Including
o
Medical underwriting guidelines
o
Financial underwriting thresholds
o
Reinsurance treaty rules and limits
Ensure That Prompts And AI Outputs Reflect
o
Risk appetite and underwriting philosophy
o
Market-specific regulatory and product requirements
Work closely with underwriting SMEs to validate AI behavior and outputs
AI-Orchestrated Underwriting Journey Design
Work with AI Engineers to design end-to-end decision flows that coordinate multiple AI agents (ingestion, structuring, quality checks, decision support)
Define sequencing, triggering, fallback handling, and escalation to human underwriters
Establish human-in-the-loop mechanisms for complex or low-confidence cases
Work with AI and tech teams to launch the new AI solutions developed
Agentic AI Integration & Prompt Alignment
Work closely with AI and data teams to define how AI agent outputs are interpreted and consumed
Align logic frameworks with prompt engineering strategies for consistent outputs
Define confidence thresholds and control mechanisms to govern AI behavior
Align AI behaviour with underwriting rules engines and decision systems
Governance, Risk & Compliance
Ensure Prompt Design Adheres To
o
Internal underwriting governance frameworks
o
Auditability and traceability requirements
o
Regulatory expectations (e.g., BNM, regional insurance regulators)
Support Development Of AI Governance Controls, Including
o
Documentation of prompt logic and decision pathways
o
Monitoring for bias, drift, and inappropriate outputs
Incorporate principles of fairness, transparency, and ethical AI usage
Multi-Market Reuse & Localization
Develop reusable core logic components with localization overlays
Ensure scalability across markets with minimal rework
Continuous Improvement & Testing
Design and execute structured testing (A/B testing, case replay, scenario testing) of prompt effectiveness
Analyse discrepancies between AI outputs and human underwriting decisions
Drive Continuous Refinement Of
o
Prompt structures
o
Input data frameworks
o
AI explainability outputs
Maintain version control and performance tracking of prompt libraries
Required Skills & Experience
Core Requirements
Strong Life & Health Underwriting experience (6-9+ years)
Deep Understanding Of
Medical and financial underwriting processes
Underwriting manuals and guidelines
Reinsurance (RI) manuals, treaties, and limits
Underwriting rules engines / automated decision systems
Experience In
Complex case underwriting (medical/high sum assured preferred)
Underwriting governance, audit, and compliance frameworks
AI / Technical Understanding
Working Knowledge Of
Generative AI / Large Language Models (LLMs)
Prompt engineering concepts and best practices
AI-driven decision-support systems
Familiarity With
Rules engines and decision logic frameworks
Data inputs required for underwriting (medical, financial, product)
Ability to translate business rules into structured logic (no coding required, but logical thinking essential)
Preferred (Highly Desirable)
Exposure to:
AI governance frameworks (model risk, fairness, explainability)
Data privacy and AI-related regulations
Ethical AI and responsible use principles
Experience in transformation initiatives (AI, digital underwriting, automation programs)
High attention to control design and risk management
Architecture & Technology Management
Location: Kuala Lumpur, Malaysia
Role Type: Individual Contributor
Domain: Life & Health Underwriting Transformation (AI & Agentic Systems)
Role Purpose
This role is responsible for designing, developing, and optimising prompt frameworks and AI-driven decision-support capabilities within the AI-enabled New Business Underwriting (NB UW) program.
The role sits at the intersection of Life & Health underwriting expertise and Generative AI, ensuring that AI outputs are clinically sound, risk-aligned, explainable, and regulator-ready. The individual will translate using internal underwriting manuals, reinsurance (RI) guidelines, and decision rules into structured prompts and AI workflows, enabling scalable, consistent, and high-quality underwriting outcomes across markets.
Key Responsibilities
Translation of UW Knowledge into AI Logic
Codify Underwriting Expertise Into Structured Logic Including
o
Medical underwriting guidelines
o
Financial underwriting thresholds
o
Reinsurance treaty rules and limits
Ensure That Prompts And AI Outputs Reflect
o
Risk appetite and underwriting philosophy
o
Market-specific regulatory and product requirements
Work closely with underwriting SMEs to validate AI behavior and outputs
AI-Orchestrated Underwriting Journey Design
Work with AI Engineers to design end-to-end decision flows that coordinate multiple AI agents (ingestion, structuring, quality checks, decision support)
Define sequencing, triggering, fallback handling, and escalation to human underwriters
Establish human-in-the-loop mechanisms for complex or low-confidence cases
Work with AI and tech teams to launch the new AI solutions developed
Agentic AI Integration & Prompt Alignment
Work closely with AI and data teams to define how AI agent outputs are interpreted and consumed
Align logic frameworks with prompt engineering strategies for consistent outputs
Define confidence thresholds and control mechanisms to govern AI behavior
Align AI behaviour with underwriting rules engines and decision systems
Governance, Risk & Compliance
Ensure Prompt Design Adheres To
o
Internal underwriting governance frameworks
o
Auditability and traceability requirements
o
Regulatory expectations (e.g., BNM, regional insurance regulators)
Support Development Of AI Governance Controls, Including
o
Documentation of prompt logic and decision pathways
o
Monitoring for bias, drift, and inappropriate outputs
Incorporate principles of fairness, transparency, and ethical AI usage
Multi-Market Reuse & Localization
Develop reusable core logic components with localization overlays
Ensure scalability across markets with minimal rework
Continuous Improvement & Testing
Design and execute structured testing (A/B testing, case replay, scenario testing) of prompt effectiveness
Analyse discrepancies between AI outputs and human underwriting decisions
Drive Continuous Refinement Of
o
Prompt structures
o
Input data frameworks
o
AI explainability outputs
Maintain version control and performance tracking of prompt libraries
Required Skills & Experience
Core Requirements
Strong Life & Health Underwriting experience (6-9+ years)
Deep Understanding Of
Medical and financial underwriting processes
Underwriting manuals and guidelines
Reinsurance (RI) manuals, treaties, and limits
Underwriting rules engines / automated decision systems
Experience In
Complex case underwriting (medical/high sum assured preferred)
Underwriting governance, audit, and compliance frameworks
AI / Technical Understanding
Working Knowledge Of
Generative AI / Large Language Models (LLMs)
Prompt engineering concepts and best practices
AI-driven decision-support systems
Familiarity With
Rules engines and decision logic frameworks
Data inputs required for underwriting (medical, financial, product)
Ability to translate business rules into structured logic (no coding required, but logical thinking essential)
Preferred (Highly Desirable)
Exposure to:
AI governance frameworks (model risk, fairness, explainability)
Data privacy and AI-related regulations
Ethical AI and responsible use principles
Experience in transformation initiatives (AI, digital underwriting, automation programs)
High attention to control design and risk management
Architecture & Technology Management
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