Drive strategic planning, governance, and stakeholder management by developing and implementing a roadmap for AI and GenAI initiatives, establishing governance frameworks and policies, monitoring compliance, and engaging with business leaders, IT teams, and other stakeholders to promote the benefits of AI technologies.
Design, develop, and maintain AI-powered applications across transport use cases including public transport operations, traffic management, and road operations.
We are looking for AI Engineers for a strategic initiative to build Agentic AI use cases around Trading Surveillance. Ideal candidate is someone with strong pyspark background coupled with proven experience build Agentic AI pipelines for code conversion from Q KDB to Pyspark.
Perform end-to-end accounts payable (AP) processing, including invoice verification, three-way matching (PO–DO/GRN–Invoice), and timely posting in the accounting system.
Contribute to and help shape the product strategy for your assigned product or feature area, ensuring alignment with the broader AI Programme goals and national digital ambitions.
Lead OS Implementation: Lead the design and implementation of the ioshii innovation OS, integrating operational information, tasks, communications, SOPs, and management reporting.
Design, build and deploy intelligent single / multi-agentic application that leverage GenAI models (e.g. LLMs) and perform task decomposition, planning and execution.
Design and conduct systematic red-teaming and risk assessments of GenAI and multi-agent systems, covering adversarial attacks, hallucinations, privacy leakage and performance across diverse scenarios
Collaborate with product owners, engineering teams and industry partners throughout the product development lifecycle, from concept and prototyping to testing, deployment, operationalisation and product end-of-life.
Own end-to-end planning, prioritisation, and tracking for the AI/ML, GenAI, CV, Optimization, Digitalization, Data Engineering, and Data Science portfolio — scope, milestones, resourcing, and critical path.
Drive foundational machine learning research in model robustness, continual learning, interpretability, and multiobjective optimization to advance trustworthy AI.
Serve as the lead researcher for regional AI safety research, defining and driving a foundational research agenda in AI alignment and developing advanced computational intelligence technology to adapt to new trends and threats.and socio-technical systems.