Introduction Our Client is looking for an Entry-Level AI Engineer to join the Data Science and Engineering team within their global IT Hub, driving the industrialization of new AI technologies and concepts.

This role centers on implementing AI pilot use cases, connecting enterprise data to Large Language Models (LLMs), and supporting AI agent development to enable domain IT squads to scale solutions across the business.

Working under direct supervision, you will apply formal machine learning knowledge, hands-on Python development, and prompt engineering to build, test, and integrate generative AI capabilities into enterprise systems.

LLMs, RAG & Prompt Engineering: Foundational understanding of Large Language Models in production, experience designing prompt workflows and guardrails, and familiarity with Retrieval-Augmented Generation (RAG) concepts. Hands-on Python & AI Testing: Solid Python programming skills and Git version control, with the ability to design test plans measuring AI output quality, latency, relevance, and hallucinations. Enterprise Integration & Enablement: Supporting the development of AI agents (e.g., Copilot, LangGraph, Semantic Kernel) and assisting business units in embedding AI tools into platforms like SAP, ServiceNow, and Microsoft Teams.

Position Details:

Contract Dates: 01-11-2026 to 31-12-2029 Location: Midrand / Menlyn / Rosslyn / Home Office Rotation Level: Entry

Duties & Responsibilities Key Responsibilities:

RAG & Agent Development: Support the design and implementation of RAG pipelines and AI agents using frameworks such as Copilot, LangGraph, and Semantic Kernel. Enterprise AI Integration: Assist in connecting AI components and LLM services to enterprise platforms, including SAP, ServiceNow, SharePoint, and Teams. Evaluation & Testing: Develop and run evaluation test suites to benchmark output quality, detect hallucinations, and measure response latency. Discovery & Enablement: Participate in customer discovery sessions with business units to understand pain points, refine prompts, and define success criteria for pilot AI use cases. Monitoring & Collaboration: Assist in setting up basic monitoring for model performance and data drift under the guidance of senior AI engineers and solution architects.

Important Application Details

Location & Relocation

Applicants based outside of Gauteng must be willing to relocate to Midrand/Menlyn/Rosslyn. Please note that relocation to the province will be at the candidate's own cost.

Eligibility & Legal

Citizenship: South African citizens and residents are preferred. Work Permits: Candidates with valid work permits will be considered. Privacy: By applying, you consent to being added to our database and receiving updates until you unsubscribe.

Application Status

If you do not receive a response within 2 weeks, please consider your application unsuccessful.

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Desired Experience & Qualification Qualifications & Experience:

Postgraduate degree (Master's or higher) in Computer Science, Engineering, Statistics, or a closely related field. Demonstrable coursework, academic projects, or internships involving LLMs, Natural Language Processing (NLP), or applied Machine Learning. Strong foundational programming skills in Python and practical familiarity with AI/ML SDKs and toolchains.

Essential Skills & Technologies:

Generative AI & Core Fundamentals:

Foundational knowledge of Large Language Models (LLMs) and their deployment in production environments. Practical experience with prompt engineering, workflow design, and safety guardrails. Understanding of Retrieval-Augmented Generation (RAG) architectures and connecting LLMs to unstructured documents/databases. Basic software development in Python (Python 3.x) and version control using Git.

Testing, Data & Communication:

Ability to design and execute test plans for AI systems, evaluating latency, accuracy, and output quality. Knowledge of data handling best practices, security awareness, and privacy considerations. Strong analytical, problem-solving, and communication skills to collaborate with technical squads and business users.

Advantageous Skills:

Hands-on exposure to agent frameworks such as LangGraph, Semantic Kernel, or Microsoft Copilot Studio. Experience implementing RAG pipelines and vector search stores (e.g., FAISS, Pinecone, Milvus). Familiarity with LLM evaluation metrics (measuring hallucinations, relevance, ground truth alignment). Exposure to cloud platforms (AWS, Azure, GCP) and MLOps/MLOps-lite model monitoring practices. Familiarity with integrating AI components with enterprise applications (SAP, ServiceNow, SharePoint, Teams). Understanding of basic data engineering (ETL, data preprocessing, feature extraction) and CI/CD pipelines.

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AI Engineer (Contract) - Gauteng/Hybrid - ISB1501071

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