We are looking for an AI Engineering Manager to join our team in Hong Kong to help lead the design and delivery of AI-powered solutions for our clients. This role combines hands-on technical expertise, designing solution architecture, consulting delivery, and team leadership.
AI Solution Design & Delivery
- Lead the design, development, and deployment of AI solutions for clients across multiple industries.
- Build applications powered by LLMs, RAG pipelines, vector databases, semantic search, document intelligence, summarization, and workflow automation.
- Design and implement agentic AI systems, including tool calling, orchestration, memory management, and human-in-the-loop workflows.
- Ensure AI solutions are aligned with client objectives, performance requirements, security standards, and cost considerations.
Engineering & Architecture
- Provide technical leadership across the AI engineering lifecycle, from prototyping through to production deployment.
- Architect scalable backend systems, APIs, microservices, and cloud-native AI applications.
- Work with frameworks and tools such as Python, LangChain, LlamaIndex, Hugging Face, PyTorch, FastAPI, Flask, Docker, and Kubernetes.
- Deploy industry-standard AI solutions on cloud platforms such as AWS, Azure, GCP, Alibaba Cloud, or Tencent Cloud.
MLOps, GenAIOps & Production Readiness
- Drive MLOps and GenAIOps best practices, including CI/CD, testing, monitoring, evaluation, and production support.
- Establish evaluation frameworks for LLM applications, including relevance, explainability, factuality, hallucination risk, latency, cost, and robustness.
- Ensure AI systems are production-ready, scalable, secure, maintainable, and aligned with operational requirements and industry standards.
Consulting & Client Leadership
- Work directly with clients to understand business challenges, identify AI opportunities, and translate requirements into solution designs.
- Lead client workshops, technical discovery sessions, architecture reviews, and solution demonstrations.
- Communicate complex AI and technical concepts clearly to both technical and non-technical stakeholders.
- Support sales, pre-sales, and proposal development by shaping technical solutions, delivery plans, estimates, and narratives.
- Advise clients on AI adoption, responsible AI, operating models, governance, and technology strategy.
Team Leadership & Delivery Management
- Lead small to medium-sized engineering teams in the delivery of AI and GenAI projects.
- Mentor AI engineers, software engineers, and junior consultants through technical guidance, code reviews, and structured feedback.
- Coordinate across data science, engineering, product, cloud, security, and business teams to ensure successful delivery.
- Promote engineering excellence, documentation, reusable assets, knowledge sharing, and continuous improvement.
Minimum Qualifications
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related technical field.
- 6+ years of relevant experience in AI engineering, MLOps, DevOps, GenAIOps, data engineering, or applied AI delivery.
- Experience working in a consulting, client-facing, or professional services environment is strongly preferred.
- Hands-on experience designing and delivering AI/ML solutions in production or production-like environments.
- Strong programming skills in Python and experience with modern AI/ML frameworks and techniques such as PyTorch, Hugging Face, LangChain, LlamaIndex, and AI orchestration platform such as n8n.
- Experience with cloud-based AI services and platforms, such as AWS/Bedrock, Azure/Foundry, GCP/Vertex, Alicloud/PAI, Tencent Cloud/TI, Databricks, or similar providers.
- Strong understanding of backend engineering, APIs, microservices, containerization, and cloud-native architecture.
- Familiarity with MLOps or GenAIOps practices, including CI/CD, monitoring, model evaluation, observability, and production support.
- Excellent communication skills with the ability to explain complex technical concepts to senior stakeholders, business users, and technical teams.
- Strong problem-solving ability, business acumen, and comfort working in ambiguous client environments.
- Fluency in English is required. Fluency in Cantonese is highly preferred for the Hong Kong market. Mandarin or other Asian language proficiency would be advantageous.
Preferred Qualifications
- Experience leading technical teams or managing AI engineering workstreams.
- Experience delivering enterprise AI solutions across sectors such as banking, insurance, energy, or retail & consumer goods.
- Experience with agent frameworks, , multi-agent orchestration, memory architectures, and workflow automation, on-prem and on cloud LLM deployments
- Experience with Docker, Kubernetes, Terraform, CI/CD pipelines, and modern DevOps practices.
- Familiarity with security, data privacy, model risk management, Responsible AI, GDPR, SOC2, or AI governance frameworks.
- Experience using AI-native engineering tools such as GitHub Copilot, Cursor, Claude Code, or similar tools.
- Experience supporting business development, proposals, solution estimation, or client presentations.
This Role Is Right for You If You Like To
- Work on high-impact AI and Generative AI projects across different industries.
- Be client-facing and operate with autonomy in a consulting environment.
- Build practical AI solutions that move beyond proof-of-concept into real production use.
- Collaborate with diverse teams across data science, software engineering, cloud, product, and business consulting.
- Mentor engineers and contribute to the growth of a high-performing AI team.
- Stay close to emerging AI technologies while focusing on business outcomes and delivery excellenceGrow your career in a fast-moving, international, performance-driven consulting environment.
Sia is an equal opportunity employer. All aspects of employment, including hiring, promotion, remuneration, or discipline, are based solely on performance, competence, conduct, or business needs.