AI Engineer (Full Stack)

About

Are you an engineer who prioritizes production-grade code over experimental prototypes? We are looking for a Full Stack AI Engineer to design, build, and deploy scalable, AI-enabled solutions that integrate directly into enterprise workflows.

This is a hands-on role focused on building real-world applications using LLM orchestration, agentic architectures, and robust retrieval systems.

Compensation & Logistics

• Rate: R500 – R650 per hour (Experience dependent)
• Location: Rosebank, Johannesburg
• Model: Hybrid
• Duration: 6-Month Contract

The Role

You will operate across the full AI delivery lifecycle—from data preparation and knowledge engineering to LLM orchestration and application development. You’ll be responsible for building "intelligent capability patterns," including multi-agent frameworks and RAG-based systems, primarily within an AWS ecosystem.

Key Responsibilities

• Full Stack Development: Build end-to-end AI applications, including backend services (Python), APIs, and user-facing components.
• AI & LLM Engineering: Design LLM workflows, tool-calling logic, and structured outputs. Build and integrate AI agents with defined execution logic.
• Knowledge Engineering: Develop RAG solutions, ensuring AI outputs are grounded, explainable, and audit-ready.
• Data & Cloud Integration: Build data pipelines for AI consumption and deploy via AWS (Lambda, Bedrock, SageMaker).
• Engineering Standards: Maintain high-quality, OO Python code within CI/CD pipelines.

Candidate Requirements

• Experience: 4–5 years in Software/Full Stack Development, ideally within Financial Services or similarly regulated environments.
• Core Tech: Expert-level Python (Production-grade) and AWS-native architectures.
• AI Specialization:
  • Hands-on experience with LLM platforms (OpenAI, Claude, Gemini).
  • Deep understanding of RAG, vector search, and embeddings.
  • Experience with orchestration patterns and multi-agent frameworks.
  • Familiarity with Model Context Protocol (MCP) or similar open standards is a major plus.
• Delivery: Experience with both "Pro-code" (complex AI builds) and "Low-code" (Power Platform/Copilot Studio) for rapid automation.

Why Apply?

This isn't about isolated R&D; it’s about moving AI into the core of the enterprise. You’ll have the autonomy to design reusable engineering patterns that set the standard for how AI is deployed at scale.

Apply now to join a team focused on delivering high-value, production-ready AI.