Artificial Intelligence Engineer

Key responsibilities

• Data services & integrations: Design, implement, and maintain secure data ingestion and transformation services that connect to external monitoring and enterprise systems via well-defined APIs.
• Analytics features: Implement modular analytics and machine-learning components for issue detection, performance assessment, and optimization; version and document these components for reuse.
• Outputs & interfaces: Define consistent output contracts (metrics, recommendations, reporting artefacts) to ensure downstream users and systems can consume results reliably.
• Reliability & operations: Ensure services are observable, well-tested, and resilient; contribute to runbooks and operational dashboards as the platform scales.
• Collaboration & documentation: Translate domain requirements into technical designs; participate in design reviews; produce clear documentation for architecture, workflows, and interfaces.
• Security & governance: Apply appropriate data governance practices for regulated environments, including access control, auditability, and data quality.

Candidate profile

Essential

• Strong software engineering background (Python preferred).
• Hands-on experience building data processing systems (batch and/or streaming) and integrating with external systems via REST/GraphQL.
• Practical familiarity with ML libraries and time-series or event data.
• Proficiency with testing, CI/CD, containers, and a major cloud platform.
• Clear communication and the ability to work effectively with product, data, and domain specialists.
• For Malaysian citizen only to cater the Malaysian laws, regulations & clients.

Advantageous

• Experience in energy, sustainability, industrial operations, or other asset-intensive domains.
• Exposure to MLOps (model training pipelines, monitoring, lifecycle management).
• Awareness of data privacy and reporting considerations relevant to ESG/carbon disclosures.