Artificial Intelligence Architecture & Engineering Technical Leadnew

Job Description

To work with business stakeholders to identify and deliver on new AI initiatives. To apply deep domain expertise to shape/influence the AI-thinking in the organisation through thought leadership; enabling the successful adoption and acceleration of AI and ML across Standard Bank Group (SBG), ensuring the needs of stakeholders are correctly understood and addressed.

Qualifications

Type of Qualification: Post Graduate Degree
Field of Study: Information Technology

Experience Required
Software Engineering
Technology
5-7 years
Experience in the AI and ML area.

AI Portfolio Delivery & Architecture
• Own end-to-end technical delivery of all priority AI initiatives -Project Aqua (Call AI), SALT Fraud Detection, Email Triage Agent and Hyper-personalisation -ensuring quality, velocity and governance standards are met.
• Define and own the SBIB AI reference architecture across AWS (Bedrock, Lambda, S3), Azure (OpenAI, AI Foundry, Document Intelligence, AI Search) and Power Platform.
• Drive productionfrom PoC through to monitored, governed production with CI/CD pipelines, model cards, drift monitoring and release management.
Ensure all solutions meet AITC, MAC and Responsible AI requirements and maintain a live solution architecture register.

Platform, Cloud & Data
• Establish and maintain a shared AI sandbox environment, define the AWS-to-Power Platform interoperability pattern, and manage ADLS, vector stores and embedding pipelines.
• Architect the managed data tier to replace SharePoint as the AI storage layer, enabling retrieval-augmented generation, pipeline monitoring and self-service data consumption.

Process Analyst Capability Uplift -AI Engineering Transition
• Design and execute the structured AI upskilling programme for the three process analysts transitioning into AI engineering roles, covering AI fundamentals, prompt engineering, Power Platform AI Builder, cloud-native patterns and live delivery pairing.
• Define individual learning pathways, assess competency progress and produce a team competency roadmap with milestone gates tied to the 18–24 month delivery plan.

Governance, Standards & Coaching
• Establish AI engineering standards: coding standards, testing protocols, model evaluation frameworks and deployment checklists across the function.
• Coach junior AI engineers and transitioning process analysts; contribute to the SBIB AI CoP and Group-wide reuse initiatives.
 

Behavioural Competencies:

• Adopting Practical Approaches
• Articulating Information
• Checking Things
• Developing Expertise
• Documenting Facts
• Embracing Change
• Examining Information
• Interpreting Data
• Managing Tasks
• Producing Output
• Taking Action
• Team Working

Technical Competencies:

• Data Analysis
• Emerging Technology Monitoring
• IT Design Driven Development
• Knowledge of Banking & Financial Service
• Systems Design
• Trouble Shooting
• Use of Libraries and Frameworks

Additional Information