Job Summary
We are currently seeking a GenAI Solution Lead to join our team. This role is responsible for leading the Generative AI scene within APAC and blends technical leadership (60%) with product engineering (40%), requiring deep full stack and Generative AI expertise, stakeholder management, and a steadfast focus on quality, compliance, and scalability.
Responsibilities
Technical Leadership (60%)
- Regular audit of vendor-developed Generative AI solution for their architecture feasibility, code quality, scalability, and security.
- Guide technical design and development processes to ensure adherence to Responsible and Ethical Generative AI principles and Generative AI engineering best practices (e.g. prompt engineering standards and testing framework).
- Conduct architecture review and analysis ranging from solution to code level for current and new Generative AI and/or Full Stack solutions.
- Contribute to the global and regional engineering standards, tools and frameworks relating to Generative AI and/or Full Stack engineering, partnering with other engineering leaders to integrate these standards into the software development and delivery processes.
- Develop and implement Generative AI-specific quality assurance processes and report QA metrics to business and technical stakeholders on a periodic basis.
Product Engineering (40%)
- Play the role of Lead Generative AI Coach to advocate for Responsible and Ethical Generative AI design within the regional product teams (across the enterprise), and mentor and train multi-functional teams on Generative AI practices, including prompt engineering and risk mitigation strategies.
- Influence vendor selection strategy for Generative AI capabilities to ensure the best technology partners, solutions and innovations are brought into the organization.
- Own end-to-end solution delivery, ensuring on-time, high-quality outcomes with risk mitigation plans.
- Stay on top of the newest technology trends in AI/ML and full stack development, applying these insights to push the boundaries of our practices and processes.
Requirements
- Tertiary education in fields such as Computer Science, Data Science, Information Systems, or Information Technology is preferred. Background in AI/ML/DS through coursework, specialization, postgraduate studies, or executive education is considered a valuable addition.
- Demonstrated ability in software engineering, with emphasis on Generative AI initiatives ranging from using LLM APIs, conduct prompt engineering and set up LLM operations.
- Proficiency in either Javascript, Typescript (or Python) and LLM frameworks (e.g. Langchain, Langgraph, etc).
- Proficient in working within a DevOps culture, applying Git-based workflows and performing code reviews alongside CI/CD pipeline evaluations for seamless integration and deployment.
- Proven track record managing software engineering projects, and ability to lead diverse teams and collaborate effectively across different functions.
- Experience contributing to discussions about new standards and revisions to existing ones.
- Experience in mentoring, coaching, and guiding other technology professionals.
- Certifications in Cloud Architecture (E.g. AWS or Azure) and SCRUM Mastering (CSM/PSM) will be advantageous but not required.
