【TW Life】Sub-Manager, AI Engineer

Role Summary
Provide technical leadership for AI engineering initiatives, driving architecture direction, solution delivery, and cross-functional alignment for enterprise AI applications. This role remains development- and solution-oriented, with limited emphasis on administrative people management and stronger focus on technical leadership, execution quality, and business impact.
Key Responsibilities

- Lead the design, development, and deployment of enterprise-scale AI/LLM applications and platforms.

- Define technical direction and solution architecture for AI initiatives involving LLMs, RAG, MLOps, and enterprise integration.

- Drive end-to-end delivery across multiple AI projects, ensuring technical quality, scalability, reliability, and alignment with business objectives.

- Partner with business, product, and technical teams to shape AI opportunities into implementable solutions.

- Provide technical leadership in architecture review, design decisions, implementation approach, and engineering standards.

- Guide team members on complex technical issues, solution design, and delivery execution.

- Oversee prioritization, technical planning, risk identification, and execution tracking across AI initiatives.

- Promote strong software engineering discipline, including coding standards, testing, observability, documentation, and secure development practices.

- Evaluate emerging AI technologies and recommend practical adoption strategies to enhance enterprise AI capability.

- Support team capability building through coaching, technical mentoring, and knowledge sharing.

Qualifications
- Bachelor’s degree in Computer Science, Computer Engineering, Data Science, Applied Mathematics, Statistics, or related fields; Master’s degree preferred.

- 3+ years of experience in software development and machine learning, including 2+ years in AI/LLM engineering or technical leadership roles.

- Proven experience leading the architecture and delivery of production-grade AI/LLM systems.

- Strong hands-on knowledge of Python, ML/LLM frameworks, cloud platforms, APIs, and MLOps practices.

- Deep understanding of distributed systems, AI solution architecture, enterprise integration, and secure SDLC practices.

- Experience driving cross-functional solution delivery and influencing both business and technical stakeholders.

- Strong technical judgment, execution focus, and solution-oriented leadership capability.
★ Recruitment Process Notice
• Please note that interview coordination for the next stage will be handled by our offshore Service Hub. All interview-related communications — including availability confirmation and interview invitations — will be conducted via email only.
• As phone contact is not available at this stage, kindly check your email regularly (including spam or junk folders) to avoid missing important updates.

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