Partner with Operations and Policy teams to design intelligent human-in-the-loop review interfaces, leveraging generative AI assistants to speed up analyst workflows and reduce manual cognitive load.
This role coordinates end-to-end AI solution integration across data sources, enterprise platforms, legacy systems and business applications. It provides technical alignment across business stakeholders, Product Owners, AI engineers, software developers, data teams, platform teams, IT and network domains.
Serve as the regional subject matter expert on AI governance, advising product owners, engineering leads, and senior stakeholders on risks, safeguards, and regulatory implications specific to APAC markets.
This role sits across platform engineering, ML/LLMOps, IT infrastructure, finance and procurement teams. Success will involve improving cost attribution, utilisation and efficiency across AI workloads while establishing consistent FinOps practices and reporting for projects, teams and applications.
The role provides technical authority across AI platform strategy, foundation models, agentic AI, model lifecycle management, AI engineering frameworks and platform capabilities. It works closely with Enterprise Architecture, AI Platform Engineering, AI Platform Operations, Cybersecurity, AI Solution Architects and business stakeholders. Success means continuously evolving an interoperable, reliable and enterprise-ready AI platform while providing technical direction to architects and engineers.
Find the “so what”: Move beyond descriptive reporting to identify trends, drivers, anomalies, risks and opportunities, and articulate their implications and potential actions.
Develop and deliver training and support certification and qualification programs in AI and robotics, including course content, instruction, and assessment and credential development aligned to the relevant standards.
Steer artificial-intelligence delivery specifically. You agree stop, pivot and scale criteria with the sponsor before a proof of concept starts. A solution moves to production only when evaluation results meet the agreed threshold and the model-risk and data-privacy sign-offs are in place. You also design human review steps with the client's process owners.
Work within established AI-native engineering workflows, collaborating with AI agents across implementation, testing, debugging, and documentation while validating every output.