Discovery is looking for an AI Engineer to identify opportunities within our Unit of Work where Automation and Agentic AI can optimize systems, improve processes, and create efficiencies. You will provide guidance on solution integration, ensure outputs follow governance and legislation, and contribute to IT leadership.
What You'll Do
- Build, support, and evolve intelligent systems that drive technology and business improvement, automation, and workflow efficiency.
- Design, develop, and operationalize AI-powered solutions that optimize the end-to-end Collections and Recoveries Unit of Work.
- Consult and provide advice on the use of multiple technologies to address the bank's needs, including deploying, supporting, and configuring them.
- Stay abreast of developments in your field of expertise to ensure personal and professional growth.
- Break down components of end-to-end design and define logical units of work.
- Validate individual design components and integrate them into an end-to-end design.
- Ensure the test strategy covers the full end-to-end design.
- Provide integration solutions and validate technical component designs.
- Review and approve component designs.
- Consult on the resolution of high-impact problem-solving.
- Build end-to-end design and release to stakeholders.
- Ensure alignment to IT strategy and architecture roadmaps.
- Lead end-to-end design on projects.
- Ensure awareness of Group Technology initiatives and standards.
- Enable skilling and corrective action by sharing knowledge and industry trends with the team.
- Obtain buy-in for developing new or enhanced processes to improve stakeholders' businesses.
What We're Looking For
- Advanced Diplomas or National 1st Degrees.
- Accreditation where formal expert certification on technology is available (JMP, MMP, or equivalent).
- 10-15 years of experience in an IT environment across infrastructures, with at least 2 years in a senior role from feeder areas.
Nice to Have
- Emerging Technology certifications in AI and Cloud (Azure).
Technical Stack
- Machine Learning (ML) – model development and deployment.
- Natural Language Processing (NLP) – email and document parsing.
- AI Builder / Copilot Studio – Power Platform AI tools.
- Data Engineering – ETL pipelines, cleansing, and enrichment.
- Prompt engineering and LLM Operations – especially for building, fine-tuning, and deploying LLM-powered solutions.
- Model Evaluation, Observability & Responsible AI – experience with model monitoring, drift detection, explainability, and responsible AI practices (bias detection, fairness, transparency).
- Power Automate / Power Apps – workflow orchestration.
- RESTful APIs, Azure Functions / Logic Apps – serverless automation.
- Kafka/Elastic/Queue skills.
- Cloud Platforms – Azure (preferred), AWS.
- Dataverse / D365 – data modeling and integration.
- Java / .NET – backend development.
Embrace the Nedbank vision and values, leading by example.
