AI Product Engineer

What will you do?

MiWay is seeking an AI Product Engineer to design, build, deploy, and continuously improve AI-powered products. This role will work closely with business area heads, executive stakeholders, data science, technology, risk, and delivery teams to design and deliver AI solutions that create measurable business value. The AI Product Engineer bridges data science, software engineering, and product thinking. This role ensures AI solutions are robust, scalable, and aligned with user needs and business objectives. This role will form part of the CIO reporting line, reporting directly to the AI Product Lead.

What will make you successful in this role?

Minimum Qualification Required
• A relevant tertiary qualification (Bachelor’s degree or equivalent)
• Qualification in Business, Engineering, Data Science, Computer Science, or a related field
• Postgraduate qualification will be advantageous
• Product Design, Agile development, or AI related certifications will be beneficial

Minimum Experience
• Minimum 3–4 years’ experience in software engineering, machine learning and data science
• At least 2–3 years’ experience delivering AI and automation solutions in a production environment
• Proven experience delivering products or initiatives with measurable business value
• Experience operating in financial services, insurance, or a regulated environment
• Strong experience working with:
• Data science and engineering teams
• Agile delivery teams
• Senior executives and business leaders

Required Skills and Experience

Technical Skills

•    Programming: Python (required), SQL (required), Golang (Advantageous), Rust (Advantageous), JavaScript / TypeScript (Advantageous) 
•    Operating Systems
o    Linux: Experience with Red Hat, BASH commands and scripting
o    Windows: PowerShell commands and scripting
•    AI/ML: 
o    Classical ML and deep learning fundamentals
o    LLMs (e.g., ChatGPT, Claude, open-source models)
o    A good understanding of LLM architectures and transformer fundamentals
o    Knowledge grounding (RAG architectures)
o    Retrieval systems (vector databases, embeddings)
o    Prompt engineering and evaluation
o    Context orchestration and management
o    LLM QLoRA fine-tuning (SFT, DPO)
o    LLM Quantization (GGUF)
•    Frameworks: 
o    FastAPI
o    Llamacpp / Ollama
o    PyTorch and Hugging Face Transformers
o    Pandas / Numpy / H2O.ai
o    NEXT.js (Advantageous)
•    Data: 
o    SQL Server / relational databases
o    Data pipelines and ETL
•    Cloud and DevOps: 
o    Azure (preferred), AWS
o    Docker, CI/CD pipelines
•    Version control: Git

Soft Skills
•    Strong problem-solving and analytical thinking
•    Ability to bridge technical and business discussions
•    Clear communication
•    Ownership mindset

Key Deliverables

•    Production-ready AI features and services
•    Scalable AI/ML pipelines
•    Prompt libraries and evaluation frameworks
•    Monitoring dashboards and alerting systems
•    Technical documentation and architecture diagrams

Deliverables include, but will not be limited to

The AI Product Lead will be responsible for, but not limited to, the following:
AI Product Development
•    Design and implement end-to-end AI solutions (LLMs, ML models) 
•    Translate business problems into AI-driven product features and solutions
•    Build APIs, services, and pipelines to integrate AI models into production systems 
•    Develop agent-based systems (e.g., Microsoft Copilot Studio agents, automation workflows)

Model Integration and Deployment
•    Integrate ML/AI models into production environments (Azure, AWS, on-prem) 
•    Optimize models for latency, cost, and reliability 
•    Implement CI/CD pipelines for ML lifecycle (MLOps) 
•    Manage versioning of models, prompts, and datasets

Prompt Engineering and LLM Systems
•    Design, test, and refine prompts and system instructions 
•    Build RAG (Retrieval-Augmented Generation) pipelines using structured/unstructured data 
•    Evaluate LLM outputs for accuracy, hallucination, and relevance 
•    Implement guardrails and safety mechanisms

Product Thinking and Stakeholder Alignment
•    Collaborate with product leads, business stakeholders, and domain experts 
•    Convert requirements into technical designs and product features 
•    Prioritize features based on business impact and feasibility 
•    Develop POCs and MVPs to prove initial business value 

Data Engineering and Pipeline Development
•    Build and maintain data ingestion and preprocessing pipelines 
•    Ensure data quality, consistency, and availability for AI systems 
•    Work with structured (SQL), semi-structured, and unstructured datasets 
•    Enable real-time or batch inference workflows

Evaluation, Monitoring and Observability
•    Define metrics for AI performance (accuracy, latency, user satisfaction) 
•    Implement monitoring for: 
•    Model drift
•    Prompt degradation
•    System failures
•    Build feedback loops to continuously improve AI systems

Experimentation and Continuous Improvement
•    Run A/B tests and controlled experiments on AI features 
•    Evaluate alternative models, prompts, and architectures 
•    Iterate rapidly based on user feedback

Security, Compliance and Responsible AI
•    Ensure AI systems comply with data privacy regulations and internal governance 
•    Implement: 
•    Access controls
•    Data masking/anonymization
•    Audit trails
•    Address bias, fairness, and explainability in AI outputs

Documentation and Knowledge Sharing
•    Document system architecture, APIs, prompts, and pipelines 
•    Create runbooks for deployment and troubleshooting 
•    Share best practices across engineering and data teams

Knowledge and Skills

Personal Attributes

Build a successful career with us

We’re all about building strong, lasting relationships with our employees. We know that you have hopes for your future – your career, your personal development and of achieving great things. We pride ourselves in helping  our employees to realise their worth. Through its five business clusters – Sanlam Fintech, Sanlam Life and Savings, Sanlam Investment Group, Sanlam Allianz, Santam, as well as MiWay and the Group Office – the group provides many opportunities for growth and development.

Core Competencies

Turnaround time

The shortlisting process will only start once the application due date has been reached. The time taken to complete this process will depend on how far you progress and the availability of managers. Deadline to apply: 12 June 2026.

Our commitment to transformation