Full Time Senior AI Engineer Jobs, in AFED Digital Cyberjaya - Ricebowl

Key Responsibilities

AI Platform Development

• Design, develop, and maintain AI Hub platform modules, services, and shared AI capabilities.
• Build reusable AI platform components that support multiple AI products and business solutions.
• Develop APIs, SDKs, and platform services to accelerate AI application development.
• Create standardized frameworks and platform capabilities for AI solution delivery.

AI Infrastructure & Model Management

• Deploy, manage, and optimize Large Language Models (LLMs), Machine Learning models, embeddings, and AI services.
• Manage model lifecycle including deployment, versioning, monitoring, scaling, and retirement.
• Support AI model serving, inference optimization, and resource allocation.
• Enable model governance, traceability, and operational control across environments.

AI Orchestration & Integration

• Develop AI orchestration services to support Agentic AI workflows and enterprise automation.
• Implement Retrieval-Augmented Generation (RAG) frameworks and vector database integrations.
• Manage Model Context Protocol (MCP) services and AI agent connectivity.
• Integrate AI Hub services with AI Products, EDAFY Data Platform, Product Engineering teams, and enterprise applications.
• Support API gateways, authentication services, and secure AI service consumption.

LLMOps / MLOps Engineering

• Implement LLMOps and MLOps practices for model deployment, monitoring, retraining, and operational management.
• Build CI/CD pipelines for AI and machine learning workloads.
• Support automated testing, deployment, release management, and infrastructure provisioning.
• Establish observability, monitoring, alerting, logging, and performance tracking mechanisms.

Infrastructure, Reliability & Operations

• Manage cloud and on-premises AI infrastructure environments.
• Support GPU infrastructure, resource optimization, workload scheduling, and capacity planning.
• Ensure platform availability, reliability, scalability, and disaster recovery readiness.
• Troubleshoot platform, infrastructure, model-serving, and integration issues.
• Drive continuous improvements in platform stability, security, and performance.

Security & Governance

• Implement enterprise security controls, access management, authentication, and authorization mechanisms.
• Ensure compliance with organizational governance, security, and data privacy policies.
• Maintain operational standards and platform best practices.
• Support AI governance and responsible AI implementation.

Documentation & Knowledge Management

• Maintain technical architecture documentation, API specifications, deployment guides, and operational procedures.
• Develop coding standards, platform standards, and engineering best practices.
• Provide technical support and guidance to internal teams and customer implementations.

Research & Innovation

• Research emerging AI platform technologies, orchestration frameworks, and infrastructure solutions.
• Evaluate new tools, platforms, and architectures to improve platform capabilities.
• Recommend innovative approaches to enhance AI scalability, performance, and operational efficiency.