Senior Backend Engineer (NodeJS)
ABOUT CLIENT
JOB DESCRIPTION
JOB REQUIREMENT
WHAT'S ON OFFER
CONTACT
Job Summary
Company Type:
Collaborative software
Technical Skills:
NodeJS
Location:
Ho Chi Minh - Viet Nam
Working Policy:
Onsite
Salary:
Negotiation
Job ID:
J01780
Status:
Close
Related Job:
Engineering Director
Ho Chi Minh - Viet Nam
product, transportation
- Backend
- Frontend
- Devops
Technology Leadership & System Scalability Oversee and optimize the entire tech stack & architecture to ensure high availability, security, and resilience. Lead infrastructure scaling to support a high volume of daily transactions across multiple services. Implement advanced AI and automation solutions to enhance platform performance. Improve system observability, monitoring, and disaster recovery strategies. Drive cost-efficient CapEx planning, optimizing for performance vs. budget balance. Team & Culture Building Manage and mentor a cross-functional tech team of more than 100 members (Backend, Mobile, SRE, QA, Data science…). Cultivate a high-speed, ownership-driven culture that promotes integrity, collaboration, and accountability. Develop technical leadership pipelines, ensuring top talent development and retention. Cultivate an engineering culture that embraces innovation, continuous learning, and rapid iteration. Future-Readiness & Technology Planning Define a 3-year technology roadmap aligned with business goals and market evolution. Evaluate emerging tech trends (AI, cloud, blockchain, automation) and implement relevant solutions. Collaborate with business and operations teams to align tech investments with growth strategies. Execution & Engineering Excellence Establish world-class engineering practices (CI/CD, DevOps, microservices, cloud architecture). Optimize for high performance, low latency, and fault tolerance in real-time operations. Lead technical transformations, re-architecture projects, and innovation initiatives.
Negotiation
View detailsSenior DevOps (Data Platform)
Ho Chi Minh - Viet Nam
Digital Bank, Product
- Devops
- Spark
Managing workloads on EC2 clusters using DataBricks/EMR for efficient data processing Collaborating with stakeholders to implement a Data Mesh architecture for multiple closely related enterprise entities Utilizing Infrastructure as Code (IaC) tools for defining and managing data platform user access Implementing role-based access control (RBAC) mechanisms to enforce least privilege principles Collaborating with cross-functional teams to design, implement, and optimize data pipelines and workflows Utilizing distributed engines such as Spark for efficient data processing and analysis Establishing operational best practices for data warehousing tools Managing storage technologies to meet business requirements Troubleshooting and resolving platform-related issues Staying updated on emerging technologies and industry trends Documenting processes, configurations, and changes for comprehensive system documentation.
Negotiation
View detailsSenior Machine Learning Engineer
Ho Chi Minh, Ha Noi - Viet Nam
Information Technology & Services
- Machine Learning
Creating the V1 Evaluation Platform: You will be responsible for designing and building the core backend systems for our new LLM Evaluation Platform, using Arize Phoenix as the basis for traces, evaluations, and experiments. Implementing Production Observability: You will need to architect and implement the observability backbone for our AI services by integrating Phoenix with OpenTelemetry to establish a centralized system for logging, tracing, and evaluating LLM behavior in production. Standardizing LLM Deployment Pipeline: You will be in charge of designing and implementing the CI/CD framework for versioning, testing, and deploying prompt-based logic and LLM configurations, ensuring reproducible and auditable deployments across all AI features. Providing Practical Solutions: Your role will involve making pragmatic technical decisions that prioritize business value and speed of delivery, in line with our early-stage startup environment. Collaborating with Other Teams: You will work closely with the Data Science team to understand their workflow and ensure that the platform you build meets their core needs for experiment tracking and validation. Establishing Core Patterns: You will also help in establishing and documenting the initial technical patterns for MLOps and model evaluation that will serve as the foundation for future development.