DevOps Engineer

Tech Lead Software Developer (Delphi, Oracle PL-SQL)

Ho Chi Minh - Viet Nam

Global Software Delivery Centers

In the role, you will work with a dedicated, enthusiastic team developing enhancements to a Laboratory Information Management System (a LIMS) and supporting the LIMS' multiple customers.As a Tech Lead Delphi Developer, you will: Lead Development teams in a local line management capacity reporting to the Software Engineering Manager in Europe Set targets and mentor the team/s locally Ensure quality in team development Participate in sprint planning and sprint retrospective meetings Assign and deliver development tasks requested during sprint planning Estimate the complexity and the workload Choose the most appropriate technical solution to meet the user requirements Design, develop and deploy changes to the LIMS according to the customers' and business users' requirements. Support the LIMS in collaboration with the other team members Working together with other team members (Engineers/QA) to ensure high quality of delivered solutions. Ensuring good practices and high quality standards are implemented and followed

Negotiation

Senior 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

Senior Machine Learning Engineer

Ho Chi Minh, Ha Noi - Viet Nam

Information Technology & Services

• Machine Learning

We are seeking a pragmatic Senior Machine Learning Engineer to accelerate our MLOps roadmap. Your primary mission will be to own the design and implementation of our V1 LLM Evaluation Platform, a critical system that will serve as the quality gate for all our AI features. You will be a key builder on a new initiative, working alongside dedicated Data Engineering and DevOps experts to deliver a tangible, high-impact platform. This role is for a hands-on engineer who thrives on building robust systems that provide leverage. You will be fully empowered to own the implementation and success of this project Build the V1 Evaluation Platform: Proactively own the end-to-end process of designing and building the core backend systems for our new LLM Evaluation Platform, leveraging Arize Phoenix as the foundational framework for traces, evaluations, and experiments. Implement Production Observability: Architect and implement the observability backbone for our AI services, integrating Phoenix with OpenTelemetry to create a centralized system for logging, tracing, and evaluating LLM behavior in production. Standardize LLM Deployment Pipeline: Design and implement the CI/CD framework for versioning, testing, and deploying prompt-based logic and LLM configurations, ensuring reproducible and auditable deployments across all AI features. Deliver Pragmatic Solutions: Consistently make pragmatic technical decisions that prioritize business value and speed of delivery, in line with our early-stage startup environment. Cross-functional Collaboration: Work closely with our Data Science team to understand their workflow and ensure the platform you build meets their core needs for experiment tracking and validation. Establish Core Patterns: Help establish and document the initial technical patterns for MLOps and model evaluation that will serve as the foundation for future development.

Negotiation