AI Solutions Engineer, HKD 70K - 95K x 12 + Bonus

Drive executive-level digital transformation for a global enterprise. Based directly within the Group CEO’s office, this high-autonomy role focuses on building production‑grade AI tools, automated workflows, and RAG pipelines to accelerate strategic decision‑making. If you have minimum 6+ years of experience deploying generative models, apply now to shape enterprise‑grade AI architecture.

Responsibilities

• Design and implement autonomous agents and automated pipelines to extract, structure, and synthesize data from disparate internal networks, corporate databases, and external market feeds.
• Construct low‑latency executive interfaces, reporting tools, and intuitive, clean user interfaces tailored for C‑suite interaction.
• Build and sustain robust backend services, data infrastructure, and platform components capable of supporting AI workloads at scale.
• Integrate practical forecasting methods and lightweight machine learning modelling where they measurably sharpen decision accuracy.
• Implement modern software practices, including strict version control, comprehensive testing, automated CI/CD pipelines, environment provisioning, and secrets management.
• Establish and manage MLOps/LLMOps deployment pipelines for packaging, tracking, monitoring, and rolling back live models.
• Turn abstract executive requests into rapid, bespoke proofs‑of‑concept, maturing successful iterations into fully supported enterprise services.
• Navigate standard governance channels to seamlessly transition ownership of operational ERP systems to central engineering teams while maintaining ongoing technical ownership of executive‑specific tools.
• Partner with internal Cybersecurity and Infrastructure teams to build comprehensive runbooks, incident response protocols, and long‑term support models.
• Enforce strict data protection, access controls, and environment isolation to protect highly sensitive corporate data.
• Continually refine system architecture to maximise performance, uptime, and cost‑efficiency.

Qualifications & Experience

• Minimum 6+ years of experience as a software, platform, DevOps, or data engineer with a proven track record of shipping production‑grade applications.
• Hands‑on AI/LLM expertise, including deploying generative models into active enterprise systems.
• Proven experience with agentic frameworks, Retrieval‑Augmented Generation (RAG), vector databases, and API tool orchestration.
• Advanced backend development skills, specifically building robust APIs and data pipelines that handle diverse documents, structured analytics, and external data streams.
• Expertise in Python for backend application development, data manipulation, and workflow automation, alongside comfort using foundational statistical or machine learning techniques.
• Cloud infrastructure proficiency with AWS, Azure, or GCP, specifically around deploying, scaling, and maintaining live production environments.
• Strong software discipline, including modern CI/CD, infrastructure‑as‑code, automated testing, and foundational MLOps/LLMOps workflows.
• Commitment to security and architecture compliance, ensuring systems are built safely when handling highly confidential or operational data.
• A degree in Computer Science, Engineering, Mathematics, Data Science, or an equivalent technical field.
• Fluency in written and spoken English is mandatory; proficiency in Cantonese or Mandarin is highly advantageous.
• Familiarity with advanced MLOps/LLMOps tools (e.g., MLflow, Kubeflow, model registries, and automated evaluation frameworks) is preferred.
• Experience utilising containerisation and orchestration layers (Docker, Kubernetes) is a plus.
• Prior experience designing digital tools for corporate executives, commodities trading, market research, or heavily regulated sectors is desirable.