Website Badger Holdings (Pty) Ltd
Badger Holdings is a specialised insurance and related services company. Founded in 1995, we currently employ over 700 staff members across South Africa and Australia and insure over 180 000 clients with premiums in excess of US$100 million. Through a unique blend of skills and expertise, Badg… read moreer Holdings has grown into a formidable force in the insurance landscape. We have been helping insurance and related companies to maximise their potential for almost two decades. Our success lies in establishing innovative insurance entities and partnering with great people who have excellent track records. We give them the means to grow sustainably into the future by providing expert assistance and advice on legal matters, training needs, marketing requirements and new product development. We believe that it is through partnership that companies will reach their full potential and achieve successful growth. That is why Badger Holdings embraces and encourages opportunities to establish firm, committed and longstanding business relationships. Our chairman often tells the story that inspired his vision for the group – about his friend who was about to crash in a glider plane. He prayed to be saved and felt a gentle wind lift the wings of the plane and gently help to land him. We see relationships and gentle landings in times of need as our offering.
What We Require
Non-negotiable
Demonstrated experience building and shipping AI agent systems in production: not demos, not internal tools that never went live
Ownership of an evaluation pipeline for a production AI system: you defined the metrics, built the framework, and used it to make deployment decisions
Experience debugging production AI failures: you have traced a silent agent degradation to its root cause in a live system
Proficiency in Python and LLM frameworks (LangChain, LlamaIndex, or equivalent)
RAG architecture: retrieval pipeline design, vector database implementation, chunking and embedding strategy
API design and backend integration at production scale
Secure tool access patterns for agentic systems: you know where LLM reasoning ends and deterministic enforcement must begin, and you have built the boundary between them
Experience implementing guardrails: input validation, output filtering, and execution-layer prompt injection defence
CI/CD for agentic systems: you have implemented progressive delivery pipelines for agents, including instrumentation of tool invocations and decision points, staging with regression benchmarks, and canary deployment to detect behavioural drift before full rollout
Strong Advantage
Experience in regulated financial services, insurance, or healthcare environments
Familiarity with graph-based agentic orchestration frameworks (LangGraph or equivalent), particularly durable execution and human-in-the-loop checkpointing in regulated environments
Familiarity with Azure AI tooling and services
MLOps practices: monitoring, observability, cost management for inference workloads
CRM and enterprise system integration
Educational Requirements
Bachelor’s degree in Computer Science, Software Engineering, Information Technology, Artificial Intelligence, Data Science, or a related field
OR equivalent practical industry experience building and deploying production-grade AI systems
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