AI Engineer (Python, LLM (RAG) Remote up to R800k per annum

E-Merge IT Recruitment; Johannesburg; Remote; ZAR 480,000 - 800,000; Full time

Benefits offered by this job

Remote work

Job summary

e-Merge IT Recruitment seeks a versatile AI Engineer to bridge AI research and production engineering. You will prototype models, evaluate prompting techniques, and turn successful ideas into scalable, observable AI services.

You’ll collaborate with product and full-stack teams to translate complex business goals into practical, high-performing AI solutions. The role focuses on data pipelines, vector stores, and efficient inference on our own infra, including GPU-backed deployments.

Qualifications

• 4+ years of experience building and shipping ML/AI systems in production.

Responsibilities

• Design, build, and deploy ML and LLM-based systems, including RAG pipelines, fine-tuned models, and agentic workflows.
• Own the full lifecycle of AI features: data collection and evaluation, model/prompt selection, experimentation, deployment, and monitoring in production.
• Build and maintain data pipelines, embeddings stores, and vector databases for search, retrieval, and personalization.
• Evaluate and integrate third-party model APIs and open-source models, balancing quality, latency, and cost.
• Fine-tune, train, and deploy open-source models on our infrastructure with data prep, training runs, quantization, and self-hosted inference.

Skills

Python

PyTorch

TensorFlow

LLMs

RAG pipelines

Fine-tuning

Vector DBs

Docker

Kubernetes

Cloud platforms

Tools

LangChain

LlamaIndex

Weaviate

pgvector

FAISS

CUDA

Job description

Our client is seeking a versatile AI Engineer who can bridge the gap between AI research, experimentation, and production engineering. The successful candidate will be responsible for rapidly prototyping and evaluating new models and prompting techniques, then transforming successful solutions into reliable, scalable, observable, and cost-efficient AI services. Working closely with product and full-stack engineering teams, they will translate complex and ambiguous business requirements into practical, high-performing AI solutions and production-ready features.

Responsibilities

• Design, build, and deploy machine learning and LLM-based systems, including retrieval-augmented generation (RAG) pipelines, fine-tuned models, and agentic workflows.
• Own the full lifecycle of AI features: data collection and evaluation, model/prompt selection, experimentation, deployment, and monitoring in production.
• Build and maintain data pipelines, embeddings stores, and vector databases that support search, retrieval, and personalization.
• Evaluate and integrate third-party model APIs (OpenAI, Anthropic, etc.) alongside open-source and self-hosted models, balancing quality, latency, and cost.
• Fine-tune, train, and deploy open-source models on our own infrastructure - including data prep, training/fine-tuning runs, quantization, and self-hosted inference serving at scale.
• Stay current with the fast-moving AI/ML landscape and bring back practical recommendations on tools, models, and techniques.

Qualifications and experience

• 4+ years of experience building and shipping machine learning or AI-powered systems in production.
• Strong Python skills, with hands-on experience using frameworks such as PyTorch, TensorFlow, or similar.
• Practical experience with large language models - prompting, fine-tuning, RAG, or agent frameworks (e.g., LangChain, LlamaIndex, or custom implementations).
• Hands-on experience training and fine-tuning open-source models (e.g., Llama, Mistral, Qwen) - full fine-tuning or parameter-efficient methods (LoRA/QLoRA) - and deploying them on your own infrastructure rather than relying solely on hosted APIs.
• Experience with vector databases and embedding-based retrieval (e.g., Pinecone, Weaviate, pgvector, FAISS).
• Comfort working with cloud infrastructure (AWS, GCP, or Azure) and containerized deployments (Docker, Kubernetes), including GPU-backed compute.
• Proficiency working with AI coding assistants (e.g., Claude Code, GitHub Copilot, Cursor) to accelerate development, while critically reviewing and validating AI-generated code.
• Experience with AI coding assistants such as Cursor, Claude, or similar
• Experience with AI coding assistants such as Cursor, Claude, or similar

Compensation and location

The reference number for this position is NG61533 which is a p ermanent, remote role offering a salary of up to R800k per annum salary negotiable based on experience.

Benefits

• We pay cash for successful referrals