MA
MaxisHead of Data & AI DevOps
Read straight from Maxis's careers page, verified 1d ago.Seekless can tailor your résumé to it.
Seekless can write your résumé for this posting first.
Before you apply
LocationMenara Maxis
Typefull-time
SeniorityDirector
DepartmentData
Company size1,001–5,000 people
PostedOct 6, 2026 · 4w ago
Verified live1d ago
At a glanceSummarised by Seekless from the posting.
Lead the 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
Design and secure infrastructure for autonomous AI agents, including MCP implementation, low-latency gateways, and secure sandboxes
Establish and enforce robust data governance frameworks, including lineage, automated data quality, and RBAC
Implement data masking, PII protection, and audit logging for compliance during autonomous operations
Develop and implement a comprehensive DevOps strategy, overseeing CI/CD pipelines
Establish LLMOps frameworks and telemetry for monitoring agent reasoning traces, model drift, and latency
Drive FinOps practices for cost monitoring, resource quotas, and alerting
Lead, mentor, and scale a high-performing team of DevOps, DataOps, and MLOps engineers
Skills
Data Warehouse
Machine Learning
Feature Store
Vector Database
LLM
Model Context Protocol (MCP)
CI/CD
RBAC
LLMOps
DevOps
DataOps
MLOps
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?
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. 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.
What’s next?
•
Once you’ve applied online, our team will carefully review your application. Due to a high volume of applications, we appreciate your patience to allow for a fair and timely review process.
•
Should you be shortlisted for the role, we will send you an invitation via email for a digital interview. You can also check on your application status by logging into your candidate account.
Legal
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.