Head of Data & AI DevOps Maxine · Menara Maxis · DevOps & Release Pay not stated 12d ago

Devopsroles; Malaysia; Hybrid; MYR 240,000 - 400,000; Full time

Job summary

Devopsroles in Malaysia is seeking a senior Data/DevOps leader to own the Data Warehouse architecture and the enterprise AI-ready data ecosystem. You will design, secure, and optimize the data foundation and its integration with AI/ML tools.

You will implement governance, RBAC, data masking, and audit logging while driving CI/CD for data models and AI applications. Leadership and collaboration across teams are essential.

Qualifications

• Experience in Data Warehouse architecture and governance is preferred.
• Strong background in DevOps practices and CI/CD for data and AI workloads.
• Familiarity with ML/Ops concepts, feature stores, and LLM environments is a plus.

Responsibilities

• Lead end-to-end architecture, provisioning, and management of the enterprise Data Warehouse and its underlying infrastructure.
• Architect and automate a modern data ecosystem optimised for machine learning, integrating feature stores, vector databases, and LLM environments.
• Establish data governance, RBAC, data masking, and audit logging for compliant autonomous AI operations.
• Develop and implement a comprehensive DevOps strategy with robust CI/CD pipelines for data models, AI apps, and infrastructure updates.
• Establish LLMOps observability and FinOps practices to monitor costs, token usage, and performance.
• Lead, mentor, and scale a high-performing DevOps/DataOps/MLOps team.

Job description

Are you ready to get ahead in your career?

• We want to empower you to turn your ambitions into achievements.
• We thrive in inclusiveness, diversity and embrace close collaborations for you to create impact for yourself and others.
• Together, we aim to bring the best of technology to help people, businesses and the nation to be ahead in a changing world.
• To realise our vision to become Malaysia’s leading converged solutions company, we are looking for a new talent to innovate and grow with us in a culture that values commitment, performance and possibilities.

Why does this job exist and why is it critical?

• 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. Furthermore, design and secure the infrastructure required for autonomous AI agents, including the implementation of 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 Role-Based Access Control (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.

Maxis values diverse voices & people. We hire and reward our employees based on capability & performance — regardless of ethnicity, gender, age, education, religion, nationality or physical ability.