Location: Etown Cong Hoa, Tan Binh, Ho Chi Minh City, Vietnam

Type: Full-time

Level: Senior / Team Lead

Contract: 6 months

Salary: Up to 78M

Job Summary:

We are looking for a Senior DevOps & Data Engineer to lead the design and implementationof scalable data pipelines and infrastructure, with a strong focus on Model ContextProtocol (MCP). This role combines leadership, system architecture, and hands-onengineering to support data-driven applications and model lifecycle management.

Key Responsibilities:

DevOps Responsibilities:

Lead the development and maintenance of CI/CD pipelines for model deploymentand data services.
Manage infrastructure automation using tools like Terraform, Ansible, orKubernetes.
Ensure system reliability, scalability, and security across environments.
Monitor and optimize cloud/on-prem resources and performance.
Collaborate with engineering and data science teams to streamline deploymentworkflows.

Data Engineering Responsibilities:

Design and implement robust data pipelines that support MCP-based modelcontext workflows.
Build and maintain ETL/ELT processes for structured and unstructured data.
Ensure data integrity, lineage, and traceability across model contexts.
Integrate data pipelines with model registries, versioning systems, and metadatastores.
Work closely with model developers to ensure seamless data-model interaction.

Leadership Responsibilities:

Lead and mentor a team of DevOps and Data Engineers.
Define and enforce best practices for infrastructure and data pipeline development.
Collaborate with cross-functional teams to align technical solutions with businessand modeling goals.
Provide technical guidance and hands-on support when needed.

Requirements:

5+ years of experience in DevOps and/or Data Engineering roles.
Strong understanding of Model Context Protocol (MCP) and its application in modellifecycle management.
Experience with data pipeline tools (e.g., Apache Airflow, Spark, Kafka) andorchestration frameworks.
Proficiency in scripting languages (Python, Bash, etc.) and infrastructure tools(Docker, Kubernetes).
Familiarity with model registries, metadata management, and version controlsystems.
Excellent leadership, communication, and problem-solving skills.
Bachelor's or Master's degree in Computer Science, Data Engineering, or relatedfield.

Nice to Have:

Experience with MLOps platforms and model governance frameworks.
Knowledge of data governance, compliance, and auditability in model-drivenenvironments.
Familiarity with cloud platforms (AWS, Azure, GCP) for hybrid deployments.

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