AI Engineering Manager

Job Description

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.

Qualifications

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.

Additional Information

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.