AI Engineer, Group Digital & Technology

Job Summary

As part of Group Digital and Technology (GDT), you will work closely with Digital Intelligence, Infrastructure, and Cybersecurity teams to unlock business value safely and reliably.

• Stakeholder engagement: Engage with business stakeholders to understand pain points, shape AI use cases, demonstrate prototypes, and communicate model and agent performance in clear, non-technical terms.
• AI solution design and delivery: Design and develop AI and ML solutions (based on Google AI services such as Vertex AI) to address prioritised business use cases and translate problem statements into technical designs covering data requirements, model approach, evaluation metrics, and integration patterns.
• Agentic AI development: Design and implement agentic AI workflows using Gemini Enterprise and Vertex AI, enabling AI agents to plan, reason, and execute multi-step tasks using enterprise data and internal tools/APIs.
• Google Cloud engineering: Build, deploy, and manage models using Google Cloud Platform (GCP), and architect scalable, secure AI services that meet reliability, performance, and cost-efficiency targets.
• Data collaboration: Work with data engineers to design and optimise data pipelines feeding AI workloads, including feature engineering and data quality controls.
• Security and governance: Collaborate with the cybersecurity team to implement guardrails for security, privacy and safety, and contribute to the Group’s AI governance framework by documenting model/agent behaviour, limitations, and approved use cases.

• Education: Bachelor’s degree in computer science, engineering, or a related field.
• AI/ML experience: 5 years of professional experience in software engineering, data science, or ML engineering, with a proven track record of designing, building, and deploying AI/ML solutions into production.
• LLM and agentic AI: Demonstrated experience building LLM-based applications and/or AI agents (e.g. using Gemini Enterprise, Vertex AI, or similar platforms), including prompt/workflow design, evaluation, and safety controls.
• Cloud and platform expertise: Practical experience with Google Cloud Platform, including services such as Vertex AI, BigQuery, Cloud Storage, and Cloud Run/Cloud Functions, and familiarity with MLOps/LLMOps practices.
• Soft skills and mindset: Strong problem-solving skills, ability to communicate complex technical topics in simple language, and a collaborative mindset focused on turning business problems into practical AI solutions.