AI Builder job template

RAG Engineer job description template

A RAG Engineer job template for internal knowledge bases, support answers, document retrieval, citations, and answer-quality evaluation.

Use this template

Role direction

Knowledge Base and Support RAG Engineer

Internal knowledge bases, support answers, document retrieval, and citation-backed responses.

Full template

We want to hire a RAG Engineer for internal knowledge base search, support answers, document retrieval, citation quality, evaluation sets, and long-term maintenance.

Required skills

- Python
- Vector databases
- Embeddings
- Chunking and retrieval strategy
- RAG evaluation

Optional skills

- LlamaIndex
- LangChain
- Milvus / pgvector
- Support or knowledge-management experience

Common mistakes

- Writing a generic AI engineer role without knowledge sources or evaluation boundaries
- Not naming data sources or update frequency
- Combining RAG, Agent, and full-stack ownership into one unfocused role

Compensation and work-mode advice

- State the range, negotiable range, or hidden compensation policy
- Clarify remote, hybrid, or onsite expectations
- For contract roles, add duration or weekly commitment

FAQ

Does a RAG Engineer need to train models?

Most company RAG roles start with content governance, retrieval quality, citations, permissions, and evaluation rather than model training.

What should be clarified before publishing?

Clarify knowledge sources, data permissions, support or internal-user scenarios, maintenance ownership, and quality metrics.

Open generator

Preparing the latest content.

FAQ

Does a RAG Engineer need to train models?

Most company RAG roles start with content governance, retrieval quality, citations, permissions, and evaluation rather than model training.

What should be clarified before publishing?

Clarify knowledge sources, data permissions, support or internal-user scenarios, maintenance ownership, and quality metrics.