AI Engineering Lead

Network Finance; Randburg; On-site; ZAR 1,200,000 - 2,400,000; Full time

Job summary

Network Finance in Randburg, South Africa, is seeking a Lead AI engineer to head a compact team hands-on with deep LLM integration, voice-pipeline (STT/TTS) and production-scale AI systems. You will design, deploy and govern AI/ML solutions, mento r engineers, and drive MLOps across projects.

You will work with cloud environments (Azure), Python and AI frameworks (TensorFlow, PyTorch, Scikit-learn, LangChain), while shaping API design and scalable architecture.

Qualifications

• Bachelor's/Master's in CS/AI/Engineering or related field (Masters preferred).
• 8+ years software engineering or ML experience.
• 3+ years in technical leadership or management.
• Proven experience delivering enterprise-scale AI/ML solutions.
• Experience working in Azure cloud environments.
• Strong Python and AI/ML frameworks: TensorFlow, PyTorch, Scikit-learn, LangChain.
• Experience with Generative AI, LLMs, RAG, and AI Agents.
• Strong ML algorithms, NLP, deep learning, and data modeling.
• Familiarity with vector databases, API development, and microservices.

Responsibilities

• Develop and implement AI strategies aligned with business objectives.
• Establish AI engineering standards, governance and best practices.
• Design, develop and deploy AI, ML and generative AI solutions.
• Oversee the end-to-end AI lifecycle from development to deployment and monitoring.
• Implement MLOps practices to support efficient model deployment and maintenance.
• Evaluate and adopt AI tools, frameworks and cloud technologies.

Skills

LLM integration

Voice pipeline

Python

API design

GitHub workflow

Production AI

People leadership

Azure

Kubernetes

Docker

CI/CD

Hugging Face

LangChain

NLP

Data modeling

Vector databases

API development

Education

Bachelor's/Master's in CS/AI/Data Science/Engineering

Tools

Azure

Kubernetes

Docker

CI/CD

Hugging Face

LangChain

Eval frameworks

Job description

The role: Lead a compact AI engineering team hands-on:

Must have: Deep LLM integration, voice-pipeline (STT/TTS) and text-agent experience, Python, API design, GitHub-based team workflow, production AI systems at scale, people leadership of small engineering teams.

Nice to have: Telephony platforms, collections or fintech domain, Azure, Kubernetes/Docker, CI/CD, Hugging Face ecosystem, eval frameworks.

Key Responsibilities:

• Develop and implement AI Strategies aligned with business objectives.
• Establish AI engineering standards, governance and best practices
• Design develop and deploy AI, machine learning and generative AI solutions
• Oversee the end-to-end AI lifecycle from development to deployment and monitoring.
• Implement MLOps practices to support efficient model deployment and maintenance.
• Evaluate and adopt AI tools, frameworks and cloud technologies.

Job Experience and Skill Required:

• Bachelor's Degree in Computer Science, Artificial Intelligence, Data Science, Engineering, Mathematics, or a related field (Masters Preferred).
• 8+ years of software engineering or machine learning experience.
• 3+ years in a technical leadership or management role.
• Proven experience delivering enterprise-scale AI and machine learning solutions.
• Demonstrated experience working in cloud environments (Azure).
• Strong proficiency in Python and AI/ML frameworks such as TensorFlow, PyTorch, Scikit-learn, and LangChain.
• Experience with Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AI Agents.
• Strong understanding of machine learning algorithms, NLP, deep learning, and data modeling.
• Familiarity with vector databases, API development, and microservices architecture.