Responsibilities
Implement Data & AI use cases end-to-end: scope with business stakeholders, design, build, deploy to production, and iterate based on real usage
Build and maintain data pipelines that ingest, transform, and serve data from client source systems into the platform
Develop applications and workflows on top of the platform, including ML and LLM-powered use cases
Integrate with enterprise source systems through APIs, databases, and file-based interfaces, and handle imperfect real-world data
Prototype quickly and demo working software to client stakeholders early and often
Harden solutions for production: testing, monitoring, security, documentation, and handover
Work onsite with client business and technical teams to translate ambiguous problems into buildable, measurable solutions
Codify what works into reusable components, patterns, and playbooks that make the next use case faster
Requirements
4+ years of hands-on software or data engineering experience, including shipping data or AI use cases to production
Degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience
Strong coding ability in Python and SQL, with working ability in at least one other language such as Java, Scala, or TypeScript
Experience building data pipelines with modern tooling such as Spark, Airflow, dbt, Kafka, or similar
Experience with at least one major cloud platform (AWS, Azure, or GCP) and with warehouse or lakehouse architectures
Experience integrating with enterprise systems through APIs, databases, and file-based interfaces
Able to scope ambiguous business problems into concrete technical solutions and communicate clearly with non-technical stakeholders
Able to operate independently in ambiguous, fast-moving environments
Fluent in Vietnamese and strong English communication skills
Benefits
Working location:
Sai Gon Ward (District 1), Ho Chi Minh City
Salary range:
7-10 years of experience: VND 80,000,000 - 120,000,000 gross
4-6 years of experience: VND 50,000,000 - 75,000,000 gross
Thông tin chung