Data Engineer - AI

Paracon Duties & Responsibilities

Are you ready to build the infrastructure that powers the future of South African business? Our Company is looking for a Data & AI Engineer to join our AI Factory-a locally hosted, enterprise-grade ecosystem designed to accelerate AI adoption across the region. In this role, you won't just be building models; you'll be designing and operationalizing the critical data pipelines and retrieval frameworks (RAG) that bring AI solutions to life in production environments. Our platform is a high-performance, NVIDIA-powered environment that bridges the gap between global innovation and local data sovereignty. We enable South African enterprises to either consume AI-as-a-Service or develop proprietary, scalable AI solutions-all while remaining fully compliant with local regulatory requirements. Responsibilities • Pipeline Architecture: Design, build, and maintain robust data pipelines that feed our AI models. • RAG Implementation: Lead the implementation of Retrieval-Augmented Generation (RAG) frameworks to enhance model accuracy and relevance. • Vector Database Management: Manage and optimize vector databases for efficient high-dimensional data retrieval. • Data Integrity: Oversee complex data transformations, rigorous validation, and the enforcement of data quality and governance standards. • Enterprise Integration: Seamlessly integrate AI data flows with existing enterprise data systems.

We are looking for a structured thinker who thrives on technical precision and reliable delivery. • Education: A Bachelor's Degree in Computer Science, Information Systems, or a related technical field. • Experience: 3-6 years in Software Engineering, with a strong preference for candidates who have experience in AI integration. • Technical Edge: Proven expertise in data pipeline design, RAG, and working within governed AI delivery ecosystems. • Mindset: A discipline for analytical problem-solving, commercial awareness, and a commitment to continuous improvement. • Analytical Discipline: The ability to break down complex data hurdles into scalable solutions. • Stakeholder Management: Clear communication with internal teams and external partners to ensure project alignment. • Reliability & Precision: Ensuring that production-level AI is stable, secure, and high-performing.