About the position
ENVIRONMENT:
A leading Insurance Company processes thousands of claims daily, each requiring thorough document review, validation, and processing. Their contact centre manages customer inquiries that follow predictable patterns. While their fraud detection currently relies on rules-based systems, there is significant potential to enhance it with machine learning. They face real operational challenges that AI can address, and they need someone capable of solving them responsibly. This is not about building prototypes or demos; they are seeking a professional who can deploy AI into production and ensure it runs reliably. Key focus areas include claims document extraction, fraud detection, and customer service copilots. These are mission-critical capabilities that must perform consistently every day. If you have experience shipping AI solutions to production and maintaining them, we want to hear from you.
RESPONSIBILITIES:
- Define the AI governance framework: how models get approved, tested, monitored, and retired
- Implement Azure OpenAI integrations with proper guardrails (content filtering, PII handling, audit logging)
- Build the claims AI pipeline: OCR, document classification, entity extraction, validation
- Establish prompt engineering standards and build a reusable prompt library
- Create evaluation frameworks so they can measure accuracy, latency, and cost objectively
- Implement responsible AI controls because insurance data is sensitive and regulators are watching
- Optimise AI costs. Token budgets, caching strategies, model selection. This stuff adds up fast
- Support the Contact Centre Copilot implementation
- Roll out GitHub Copilot to the development team with appropriate policies and training
- Monitor model performance in production and catch drift before it causes problems
REQUIREMENTS:
What You Bring
- You've deployed AI/ML to production and maintained it. Jupiter notebooks don't count
- 5+ years in software engineering with 2+ years focused on AI/ML
- Hands-on Azure OpenAI or OpenAI API experience
- Strong Python skills for ML pipeline development
- Experience with document AI: OCR, form recognition, NER, document classification
- Understanding of LLM patterns: RAG, fine-tuning, prompt engineering, embedding models
- Familiarity with vector databases and semantic search
- Software engineering discipline: testing, code review, documentation, monitoring
Education
- Degree or Diploma in Computer Science, Information Technology, Software Engineering, Computer Engineering, or a related technical field.
- Relevant cloud, API, or platform engineering certifications (Azure preferred) will be advantageous.
- Equivalent practical experience building and maintaining production APIs and distributed systems will also be considered.
Nice to Have
- Azure AI Services experience (Document Intelligence, Cognitive Services)
- Insurance claims processing knowledge
- Experience with AI safety and responsible AI practices
- Lang Chain, Semantic Kernel, or similar frameworks
- GitHub Copilot enterprise deployment experience
Desired Skills:
- Microsoft Azure
- Python
- Software Engineering
About The Employer:
A leading digital-first insurance provider revolutionizing the South African insurance landscape through innovation, transparency, and customer-centric technology. The company offers a comprehensive range of personal and pet insurance products, all managed through seamless online platforms designed to give customers control, flexibility, and instant access to their policies. With a strong focus on innovation, service excellence, and community impact, they continue to redefine how people experience insurance — making it simpler, faster, and more human.
