Lead AI Engineer

This is a 6 month contract role with our client in the Fintech Space.

Lead AI Engineer, you will serve as the absolute technical authority for production-grade AI solutions across our Fintech ecosystem. This is a strategic, high-impact engineering leadership position where you will translate AI strategy into buildable, scalable architecture, moving enterprise AI from isolated pilots into secure, daily production.

• AI Engineering Leadership: Set the gold standard for enterprise AI code quality, architecture patterns, API design, and observability while mentoring Full Stack AI and automation engineers.
• Solution Architecture & Delivery: Own the end-to-end technical design and deployment of high-visibility MVPs, including voice/IVR automation, finance bots, automated testing tools, and internal knowledge copilots.
• Advanced RAG & Agentic Design: Architect bulletproof Retrieval-Augmented Generation (RAG) structures and agentic workflows embedded with guardrails, evaluation frameworks, and human-in-the-loop controls.
• Model Orchestration: Define enterprise patterns for when to deploy cloud platforms (Azure AI Foundry, Azure OpenAI), commercial models (Claude), or open-source solutions using frameworks like Lang Graph, Semantic Kernel, or Copilot Studio.
• Security & Governance: Partner with Cybersecurity and Risk teams to safeguard against prompt injection and data leakage, ensuring strict alignment with data privacy laws (POPIA/GDPR).

• 8+ years in software engineering, solution architecture, or platform engineering.
• 3+ years of direct, hands-on experience building and shipping production-grade AI, automation, or advanced data platforms.
• Proven track record acting as a technical authority within large corporate or regulated environments.
• Deep proficiency in cloud platforms (preferably Microsoft Azure) and API-first engineering using Python or Type Script (FastAPI, Node.js, NestJS).
• Hands-on experience with vector databases, agentic frameworks (Lang Graph, Auto Gen), and LLM evaluation metrics (latency, cost, and hallucination tracking).

• Experience in financial services, fintech, telecommunications, or digital payment channels.
• Relevant certifications (Microsoft Azure AI Engineer Associate, Azure Solutions Architect).
• Exposure to voice AI, conversational IVR, or MLOps/LLMOps governance frameworks.