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AI Engineer, Business Operations
CollaboratorDataArtificial Intelligence26-DTO-4057
Thành phố Hồ Chí Min...thành phố hồ chí minh
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Job description
Job Description
The AI Engineer is responsible for designing, building, and deploying AI-powered applications and workflow automation solutions that solve real business problems and improve productivity, decision-making, and operational efficiency.
Working within the Digital Transformation Office (DTO), the AI Engineer will focus primarily on Generative AI, AI agents, and intelligent workflow automation, turning business requirements into reliable, production-ready AI solutions.
The role works closely with Product Managers, Business Analysts, business users, Data Engineers, and Software Engineers throughout the product lifecycle, from solution design and prototyping to production deployment, monitoring, and continuous improvement.
Key Responsibilities
The AI Engineer is responsible for designing, building, and deploying AI-powered applications and workflow automation solutions that solve real business problems and improve productivity, decision-making, and operational efficiency.
Working within the Digital Transformation Office (DTO), the AI Engineer will focus primarily on Generative AI, AI agents, and intelligent workflow automation, turning business requirements into reliable, production-ready AI solutions.
The role works closely with Product Managers, Business Analysts, business users, Data Engineers, and Software Engineers throughout the product lifecycle, from solution design and prototyping to production deployment, monitoring, and continuous improvement.
Key Responsibilities
- Design and build AI-powered applications, including AI assistants, copilots, AI agents, RAG solutions, and intelligent workflow automation.
- Develop and integrate LLM-based capabilities using foundation models, APIs, prompt engineering, tool/function calling, structured outputs, and agentic workflows.
- Build RAG and enterprise knowledge solutions, including document processing, embeddings, vector search, retrieval, context management, and integration with internal data sources.
- Integrate AI solutions with enterprise systems and workflows through APIs, databases, business applications, and automation platforms.
- Evaluate and improve AI solution quality, including accuracy, reliability, latency, cost, security, and overall user experience.
- Deploy and operate production AI solutions, including testing, monitoring, logging, troubleshooting, and continuous optimization.
- Collaborate with Product Managers, BAs, and business users to rapidly prototype solutions, validate use cases, and translate business requirements into scalable technical implementations.
Requirement
- 2–5+ years of software engineering, AI/ML engineering, or related experience, with strong hands-on development skills.
- Strong programming skills in Python and experience building production applications, APIs, and backend services.
- Hands-on experience building applications using LLMs and Generative AI, including prompt engineering, structured outputs, tool/function calling, and model APIs.
- Experience with RAG, embeddings, vector databases/search, document processing, and enterprise knowledge retrieval.
- Experience building AI agents or agentic workflows using frameworks such as LangGraph, LangChain, or similar technologies.
- Good understanding of software engineering practices, including Git, testing, API design, CI/CD, containers, logging, and monitoring.
- Strong problem-solving and collaboration skills, with the ability to rapidly prototype, experiment, and turn ambiguous business problems into practical production solutions.
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