Head of Data & AI DevOps & Platform Engineering

Maxis; Kuala Lumpur; On-site; MYR 180,000 - 240,000; Full time

Job summary

Maxis is seeking a senior data architecture and platform leadership role based in Kuala Lumpur. The successful candidate will own the Data Warehouse and its infrastructure, architect AI-ready data ecosystems, and establish governance, security, and compliance for autonomous AI initiatives.

You will drive DevOps, CI/CD, and MLOps practices while mentoring a high-performing team to deliver scalable data models and AI applications.

Responsibilities

• Data Warehouse & Infrastructure Ownership: Lead the end-to-end architecture, provisioning, and management of the enterprise Data Warehouse and its underlying infrastructure to ensure a highly scalable, performant, and resilient foundation for all analytical and AI initiatives.
• AI-Ready Ecosystem & Agentic Enablement: Architect and automate a modern data ecosystem optimised for machine learning, seamlessly integrating feature stores, vector databases, and LLM environments. Design and secure the infrastructure required for autonomous AI agents, including the Model Context Protocol (MCP) for secure agentic access to the Data Warehouse and enterprise APIs, alongside low-latency gateways and secure sandboxes for autonomous tool-calling.
• Data Governance, Security & AI Guardrails: Establish and enforce robust data governance frameworks. Implement strict data lineage, automated data quality monitoring, and granular RBAC. Ensure automated data masking, PII protection, and comprehensive audit logging are embedded to maintain compliance during autonomous AI and MCP operations.
• DevOps & CI/CD Strategy: Develop and implement a comprehensive DevOps strategy, overseeing the design and maintenance of robust CI/CD pipelines to ensure rapid, reliable, and automated delivery of data models, AI applications, and infrastructure updates.
• LLMOps, Observability & FinOps: Establish comprehensive LLMOps frameworks and telemetry to monitor agent reasoning traces, model drift, and system latency. Drive FinOps best practices by leveraging this observability to implement strict cost-monitoring, resource quotas, and alerting mechanisms, ensuring Data Warehouse compute and LLM token consumption are highly optimised, performant, and cost-efficient.
• Team Leadership & Capability Building: Lead, mentor, and scale a high-performing team of DevOps, DataOps, and MLOps engineers, fostering a culture of continuous learning and engineering excellence.

Job description

Maxis is seeking a senior data architecture and platform leadership role based in Kuala Lumpur. The successful candidate will own the Data Warehouse and its infrastructure, architect AI-ready data ecosystems, and establish governance, security, and compliance for autonomous AI initiatives.

You will drive DevOps, CI/CD, and MLOps practices while mentoring a high-performing team to deliver scalable data models and AI applications.