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.
