AI Engineer (Entry) 1071

Pay

On application

Type

Contract

Sector

IT & Internet

Closes

in 8 days

Recruiter

Mediro ICT · All jobs at Mediro ICT

About the role

Our client in Pretoria is looking for a AI Engineer (Entry) to join their team.

• Assist internal teams and business units to integrate AI solutions and tools into their systems.
• Support the development of AI agents using frameworks like Copilot, LangGraph, Semantic Kernel and relevant SDKs.
• Help design and implement RAG solutions to connect LLMs with enterprise documents and databases.
• Integrate AI components with enterprise systems such as SAP, ServiceNow, Teams, SharePoint and internal systems.
• Participate in customer discovery to understand real business processes, pain points and success criteria.
• Develop and run evaluation tests to measure hallucinations, output quality, latency and business value.
• Assist in building monitoring and alerting for AI system performance and data drift.
• Collaborate with AI engineers, solution architects and business stakeholders to deliver integrated solutions.

What they're looking for

• Qualifications/Experience:
• Postgraduate degree (Master’s or higher) in Computer Science, Engineering, Statistics or a closely related field.
• Demonstrable coursework, projects, or internships involving LLMs, NLP or applied ML.
• Strong foundational programming skills (Python) and familiarity with AI/ML toolchains and SDKs.
• Essential Skills:
• Foundational knowledge of Large Language Models (LLMs) and how they are used in production.
• Experience with prompt engineering and designing prompt workflows and guardrails.
• Familiarity with Retrieval-Augmented Generation (RAG) concepts and connecting LLMs to documents/databases.
• Basic software development skills (Python preferred) and version control (Git).
• Ability to design and execute test plans for AI systems, including quality and latency measurements.
• Strong analytical and problem-solving skills with attention to detail.
• Clear written and verbal communication skills for working with technical and non-technical stakeholders.
• Knowledge of data handling best practices, security awareness, and privacy considerations.
• Advantageous Skills:
• Hands-on experience with agent frameworks such as Copilot, LangGraph, or Semantic Kernel.
• Experience implementing RAG pipelines and vector search (e.g., FAISS, Pinecone, Milvus).
• Familiarity with evaluation metrics for LLMs (hallucination measurement, relevance, answer quality).
• Exposure to cloud platforms and deployment tooling (Azure, AWS, or GCP).
• Understanding of MLOps/MLOps-lite practices for model deployment and monitoring.
• Experience integrating AI with enterprise applications (SAP, ServiceNow, SharePoint, Teams).
• Experience with data engineering basics: ETL, data preprocessing and feature extraction.
• Familiarity with automated testing frameworks and CI/CD for AI components.