Artificial Intelligence Architecture & Engineering Technical Lead

Standard Bank Group is a leading Africa-focused financial services group, and an innovative player on the global stage, that offers a variety of career-enhancing opportunities – plus the chance to work alongside some of the sector’s most talented, motivated professionals. Our clients range from individuals, to businesses of all sizes, high net worth families and large multinational corporates and institutions. We’re passionate about creating growth in Africa. Bringing true, meaningful value to our clients and the communities we serve and creating a real sense of purpose for you.

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.

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