AI Applications Engineer: Build & Scale with AI Champions

Swire Properties Limited 太古地產有限公司

Hong Kong

Hybrid

HKD 900,000 - 1,300,000

Full time

14 days+

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Job summary

Swire Properties Limited 太古地產有限公司 is seeking a hands-on AI builder who ships production-grade AI solutions directly with business users and grows departmental AI fluency by developing AI Champions across units.

The role blends end-to-end AI delivery (discovery to production) with departmental enablement, using low-code-to-pro-code platforms. You will iterate on AI initiatives, RAG solutions, and governance in an agile environment.

Qualifications

Bachelor's degree in Computer Science or a related field.
Master's degree in AI, Data Science, or related discipline is advantageous.
5-8 years IT, digital application delivery, or technology project experience.
2-3 years AI applications, AI platforms, automation solutions, or AI capability integration within business applications.
Hands-on coding experience (Python, SQL) to build AI solutions.
Demonstrated experience training, coaching, or supporting non-technical users on a platform or tool.
Comfortable navigating ambiguity and delivering iterative solutions in Agile, Scrum, or hybrid environments.
Cloud platform knowledge and certification preferred.

Responsibilities

Personally design, build, test, and iterate AI applications and agents directly with business users.
Own solutions from discovery through production deployment, monitoring, and iteration.
Build and configure integrations using low-code-to-pro-code platforms (e.g. Copilot Studio, Power Platform, Azure AI Foundry).
Troubleshoot and refine deployed solutions based on real usage and business feedback.
Support the implementation of Agentic AI, automation, and workflow optimization initiatives.
Identify and develop departmental AI Champions per business unit, coaching them on low-code/no-code AI tools.
Create reusable templates, prompt libraries, and markdown-based knowledge assets for non-technical champions.
Collaborate with business users, technical teams, and external partners to meet business needs.
Contribute to AI governance, best practices, documentation, and operational support.
Support and mentor junior team members and departmental champions as required.
Report field learnings from both build work and champion enablement back into AI governance and the platform roadmap.