Role & responsibilities
- Define the enterprise AI architecture vision and reference patterns; align them to business goals, risk posture, and engineering standards across cloud and hybrid environments.
- Design secure, scalable AI solutions covering data ingestion, feature engineering, model training, inference, and continuous feedback loops.
- Establish integration patterns (APIs, events, microservices) to embed modelpowered capabilities into existing platforms with transparent service boundaries.
- Define enterprise-wide AI architecture guidelines, reusable components, and long-term roadmap to ensure consistency and acceleration of AI initiatives.
- Implement MLOps/LLMOps pipelines for versioning, CI/CD, approvals, and controlled promotion across environments; enforce reproducibility.
- Work closely with product owners, data scientists, engineers, security teams, and business stakeholders to ensure architecture translates into highvalue solutions.
- Enforce IAM leastprivilege with IAM Conditions, organisation policies, and scoped service accounts; integrate BeyondCorp for zerotrust access.