AIOps & Generative AI Engineer for Scalable ML Platforms

FWD Group Management Holdings Limited

Kuala Lumpur

On-site

MYR 180,000 - 300,000

Full time

14 days+

Application generator

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Job summary

FWD Group is seeking an AI Ops Engineer in Kuala Lumpur to lead the design, deployment, and operation of enterprise AI/ML solutions on the GODP. You will collaborate with Data Architects, Data Scientists, and Platform teams to build scalable AI offerings aligned with business goals and governance standards.

The role requires 5+ years in data engineering and MLOps, strong Python/Spark skills, and hands-on experience with Generative AI.

Qualifications

Bachelor's degree in Computer Science, Information Technology, Engineering, Mathematics, or a related discipline.
Minimum 5 years of relevant experience in Data Engineering, MLOps, AI Engineering, or related fields.
Strong analytical thinking, problem-solving, and troubleshooting capabilities.
Proficient in Python, Spark, and software engineering best practices.
Hands-on experience developing and deploying Generative AI, LLM-based, and Agentic AI applications.
Familiarity with metadata management.

Responsibilities

Collaborate with Data Architects, Data Scientists, Data Engineers, and Platform teams to design and deliver scalable data and AI solutions aligned with business objectives and analytical requirements.
Partner with business stakeholders to design, develop, and implement Generative AI and Agentic AI applications that drive business value and operational efficiency.
Work closely with Data Science teams to operationalize AI/ML models and integrate them into production environments.
Design, implement, and maintain MLOps pipelines to automate model training, validation, deployment, monitoring, and lifecycle management.
Support the development, optimization, scaling, and reliability of AI/ML and Generative AI solutions to ensure production readiness and operational excellence.
Ensure compliance with enterprise data governance, security, privacy, and regulatory requirements.
Drive continuous improvement initiatives through automation, performance optimization, platform modernization, and adoption of emerging AI technologies.
Provide production support for AI applications, AI models, and data pipelines, including incident investigation, root cause analysis, troubleshooting, and resolution.
Maintain comprehensive technical documentation, operational procedures, and knowledge repositories.
Mentor and guide team members, promoting engineering best practices, innovation, collaboration, and continuous learning.