AI Tech Lead

The AI Tech Lead provides expert technical leadership to design, build, and operationalize AI solutions that drive measurable business value.

Responsibilities:

• Lead and give technical direction, and best practices across GenAI and ML solutions.
• Own end-to-end delivery,from design and prototyping to production deployment and optimization.
• Ensure solution quality, security, reliability, and compliance with enterprise standards.
• Collaborate effectively with product owners and application teams to align requirements and manage dependencies.
• Champion technical clarity and communication.

Technical Leadership:

• Defines and enforces technical standards, patterns, and best practices across the AI stack.
• Ensures alignment with enterprise architecture, security policies, and regulatory requirements.
• Serves as the SME (Subject Matter Expert) for AI/ML, GenAI, and supporting technologies within the team.
• Provides hands-on guidance in design reviews and code reviews.

Delivery Ownership (Accountability: End-to-End Delivery & Solution Success):

• Accountable for delivering AI solutions that meet business objectives, not just technical completion.
• Owns the delivery lifecycle,discovery, prototyping, model training/selection, development, integration, testing, deployment, and production.
• Leads backlog technical grooming; estimates complexity, breaks down work, and directs the engineering execution plan.
• Identify potential risks related to technology initiatives and create mitigation strategies.

Knowledge Management:

• Oversee the creation and maintenance of technical documentation.
• Maintain an active knowledge base for digital solutions and AI related material and system documents.
• Gather user feedback for future improvements.

Preferred skills:

• Hands-on experience in Python and Java.
• Familiarity with REST APIs and frameworks such as FastAPI, Flask, or similar technologies.
• Experience with LLM frameworks including LangChain, LangGraph, and n8n.
• Knowledge of databases such as PostgreSQL and Cosmos DB.
• Practical experience with AWS cloud services, especially SageMaker and Bedrock.
• Strong knowledge of containerization and orchestration tools such as Docker, Kubernetes.

Qualifications:

• University graduate, preferably in IT, Computer Science or related disciplines.
• Over 8 years of working experience.
• At least 2 years of relevant experience in AI engineering.
• Practical experience with AI/MLOps practices in enterprise environments.
• Proficiency in both spoken and written English and Chinese.