Ai Engineer

AimBig Employment Pty Ltd; Kuala Lumpur; On-site; MYR 240,000 - 360,000; Full time

Benefits offered by this job

Contract: 1 year

Medical benefits

Cutting-edge AI tech

Job summary

AimBig Employment Pty Ltd seeks a Solution Architect to own AI service architectures and drive end-to-end ML/AI initiatives in a Kuala Lumpur insurance tech environment.

Lead technical direction, review designs, and mentor engineers while delivering production-grade GenAI features and AI governance across platforms.

Qualifications

• Proficiency in Python and ML frameworks (scikit-learn, XGBoost, PyTorch, TensorFlow).
• Strong grasp of generative AI and LLM techniques including prompt engineering and RAG.
• Experience training and operationalizing custom ML models end to end.
• Design and deployment on AWS with core services listed (Lambda, API Gateway, SageMaker, Textract).
• Infrastructure as Code with Terraform; AWS CDK a plus; solid MLOps understanding.
• Ability to own solution architecture and mentor engineers; lead design reviews.

Responsibilities

• Own the solution architecture for AI services and new initiatives; define integration patterns and governance.
• Provide technical leadership, mentor engineers, and uphold engineering best practices.
• Review designs and code for quality, security, and platform alignment.
• Deliver new AI projects from concept to production across fraud, extraction, and automation.
• Build and improve serverless AI pipelines on AWS; maintain observability and dashboards.

Skills

Python

ML frameworks

AWS

Terraform

MLOps

LLM techniques

Docker

Serverless

Cognition/AI governance

Leadership

Tools

SageMaker

Textract

ECR/DynamoDB

Terraform modules

Job description

• Competitive Salary
• Opportunity to work on cutting edge technology

About Our Client

A company operating in the insurance industry, located in Kuala Lumpur.

Job Description

• Solution architecture ownership. Own the solution architecture for AI services and new initiatives - make and document technology and design decisions, define integration patterns across services, and ensure solutions align with platform standards, security, and AI governance.
• Technical leadership & mentoring. Mentor and support other engineers, share knowledge across the team, and help grow AI/ML capability. Set and uphold engineering best practices through code and architecture review.
• Architecture & code review. Review designs and code from the team to ensure quality, maintainability, security, and consistency with platform standards, and provide constructive, actionable feedback.
• Deliver new AI projects. Take new initiatives from concept to production across areas such as fraud detection, document processing and intelligent extraction, underwriting automation, and AI for operations. Gather requirements, design the solution and architecture, build it on the shared platform, and hand it over as a monitored, governed production service.
• Platform engineering & IaC. Implement and enhance the AI and analytics platform using Infrastructure as Code with Terraform. Keep changes aligned with existing VPC, IAM, API Gateway, and data-layer architecture.
• End-to-end ML/AI lifecycle. Manage models across the full lifecycle. This covers training and deploying custom ML models (e.g. classification, regression, object detection / computer vision) via our SageMaker MLOps pipeline (preprocess train evaluate conditionally register), as well as integrating LLM as needed. Cover model import, training, evaluation, deployment, inference execution, monitoring, and integration of outputs into downstream applications and automation workflows.
• Serverless AI pipelines. Build scalable, serverless AI and data processing pipelines on AWS.
• Generative AI solutions. Develop and integrate GenAI features - LLM-based classification and extraction, document/case analysis, RAG, and chatbots - into operational workflows.
• Automation of core insurance operations. Support automation across: (i) data capture and verification from documents (OCR + LLM-based extraction); (ii) automated adjudication, eligibility checks, and benefit/reserve calculations; (iii) fraud/anomaly detection using ML and analytics; and (iv) workflow automation for processes such as claims assessment, payment initiation, notifications, and underwriting.
• Vendor evaluation & third-party integration. Support end-to-end vendor evaluation and procurement (RFI, RFP, selection, due diligence) and adapt third-party AI solutions into the GIMB environment, aligned with architectural principles, AI governance, and technical standards. Manage integrations with enterprise platforms, data services, and corporate systems.
• Cross-functional collaboration. Work with data engineers, business analysts, business units, and other stakeholders to gather requirements, onboard new use cases and lines of business, and integrate AI outputs into business processes and reporting.
• AI governance & Responsible AI. Support the AI governance framework: complete AI Risk Assessments before production deployment, maintain the AI Model Registry, document prompt designs and model/classification logic, keep human-in-the-loop QC workflows, and enforce data-privacy controls.
• Ground truth, evaluation & observability. Develop ground-truth datasets and labeling processes for training, evaluation, and monitoring. Compile accuracy/performance metrics and statistical analysis to drive model improvement. Implement structured logging, CloudWatch dashboards, and alarms/SNS notifications for service health, error rates, and model degradation

The Successful Applicant

• Proficiency in Python and ML frameworks/algorithms (e.g. scikit-learn, XGBoost, PyTorch, TensorFlow).
• Strong grasp of generative AI and LLM techniques: prompt engineering, structured extraction, RAG, embeddings, and integrating hosted models (Anthropic Claude, Amazon Bedrock).
• Experience training and operationalizing custom ML models end to end (data prep, training, evaluation, deployment, monitoring).
• Experience designing and deploying on AWS, hands-on with core services used here: Lambda, API Gateway, Step Functions, SageMaker, Bedrock, Textract, DynamoDB, S3, ECR, SSM Parameter Store, CloudWatch, VPC/IAM.
• Infrastructure as Code with Terraform - modules, per-environment state backends, plan/apply workflows (AWS CDK a plus).
• Solid MLOps understanding: CI/CD, model registration, monitoring, and drift detection.
• Proven ability to own solution architecture and mentor engineers, including leading design and code reviews.
• Familiarity with event-driven and serverless architectures (Lambda / Step Functions).
• Container skills: Docker (Python slim base images, Lambda container images) and image lifecycle management in ECR
• OCR and document-intelligence experience (AWS Textract, IDP pipelines).
• Computer vision / object detection experience (e.g. training and deploying detection models).
• Vector search / RAG with a vector store (e.g. pgvector).
• Data warehouse familiarity such as Amazon Redshift.
• API contract discipline with OpenAPI specs.
• Full-stack awareness for AI applications: FastAPI backends and React/Vite/MUI frontends.
• Exposure to Responsible AI practices and LLM guardrails (content filtering, confidence scoring, human review).
• AWS certifications (AI/ML Specialty, Solutions Architect) or equivalent.

What's on Offer

• Contract: 1 year (extendable)
• Medical benefits
• Opportunities to work on cutting-edge AI technologies within the BFSI industry.