Python Developer – AI Engineering - Buy-side - Financial Services
Hong Kong | Full-Time | No Relocation Support
Experience Required: 2–5 Years
Locally Based Candidates Only
My client is looking for a highly motivated Python Developer with AI Engineering experience to join our growing team in Hong Kong. This role is ideal for someone passionate about building intelligent workflow solutions, automation tools, and scalable AI‑driven applications that improve collaboration and efficiency across business functions.
You will work closely with multiple teams to design and implement solutions that streamline operations, optimize processes, and unlock productivity using Python, AI, and automation technologies.
Key Responsibilities
Develop and maintain scalable Python applications and workflow automation tools
Design AI‑powered solutions to optimize internal business processes across teams and functions
Collaborate with stakeholders to identify inefficiencies and implement intelligent automation strategies
Integrate APIs, LLMs, AI agents, and third‑party platforms into operational workflows
Build data pipelines, backend services, and internal productivity tools
Improve system performance, reliability, and scalability
Participate in solution architecture, testing, deployment, and documentation
Stay updated with emerging AI technologies and recommend practical business applications
Requirements
2–5 years of professional experience in Python development
Hands‑on experience with AI Engineering, Generative AI, or workflow automation projects
Strong knowledge of Python frameworks and backend development
Experience working with APIs, databases, and cloud platforms
Familiarity with LLMs, AI tools, vector databases, or automation frameworks is highly preferred
Strong problem‑solving and communication skills
Ability to work cross‑functionally with technical and non‑technical stakeholders
Proactive mindset with a passion for innovation and operational efficiency
Preferred Skills
Experience with OpenAI, LangChain, LlamaIndex, or similar AI ecosystems
Exposure to DevOps, CI/CD, Docker, or cloud‑native environments
Knowledge of data engineering or analytics workflows
Experience building internal tools or enterprise automation platforms
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