AI Application Engineer_ESG Consulting Office(內湖)

Your job is to turn requirements into digital services that can be deployed. We are looking for an engineer who can build AI features and put them into products, and who can independently own an AI feature across its full lifecycle, from design and development through to launch.

You will work closely with the product team to translate business needs into usable AI applications, and use modern AI development tools to accelerate delivery. This is a hands-on, fast-iterating role where you can see your work reach real users directly.

1. AI Feature Development & Delivery

• Own AI features end to end, from requirements and design to launch and operations.
• Integrate LLM APIs and services (RAG, vector databases, agent workflows) to build generative AI applications: chatbots, knowledge-base Q&A, document summarization, report generation.
• Work with the product team to turn business pain points into AI solutions that solve real user problems.
• Design prompts and data flows, balancing output quality, stability, and cost.
• Write clear technical documentation so the team can maintain and extend each feature.

2. Accelerating Development with AI Tools

• Use AI coding tools daily to improve delivery speed and quality.
• Help build the team’s AI development practices and share useful workflows.
• Stay curious about new AI tools, trying them out and assessing their practical value.

《Qualifications & Requirements》

• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or related field.
• 3+ years of experience in data engineering, platform development, or cloud data integration.
• Strong proficiency in SQL, Python/Scala, and ETL frameworks.
• Hands-on experience with cloud data platforms (BigQuery, Snowflake, Databricks, AWS S3, etc.).
• Familiarity with API development and integration (REST, GraphQL).
• Experience in agile, DevOps, and CI/CD pipelines for data engineering.
• Strong problem-solving and analytical skills, with the ability to handle complex datasets.

[Nice-to-Have]

• Exposure to ESG data and sustainability metrics.
• Familiarity with data security, encryption, and compliance in enterprise IT environments.
• Experience with data integration and quality tools across no-code, low-code platforms.

[Soft Skills]

• Strong collaboration and communication skills to work across technical and non-technical teams.
• Detail-oriented, with a focus on accuracy and compliance.
• Ability to translate business requirements into scalable data solutions.