Write a Prompt Engineer Resume That Proves Model Judgment
A prompt engineer resume built around evaluation sets, retrieval pipelines and model routing, with a sample resume and a full writing guide.
Example Prompt Engineer summary
Prompt engineer with four years of experience making language model behavior measurable. Builds graded evaluation sets first, then iterates on system prompts, retrieval and tool definitions against them. Raised support assistant accuracy from 61% to 88% while cutting tokens per request by a third. Experienced with adversarial testing for prompt injection and with routing traffic across small and frontier models to control cost.
Skills to list on a Prompt Engineer resume
- Prompt design
- Evaluation set construction
- Retrieval-augmented generation
- Embeddings and vector search
- Python
- LangChain
- Function and tool calling
- Fine-tuning and adapters
- Model red teaming
- Guardrails and output filtering
- Token and cost optimization
- A/B testing
- Annotation rubrics
- Prompt versioning
What actually gets this resume read
- Lead with the evaluation set you built, not the prompts you wrote, because measurement is what separates this role from casual chat use.
- Name the models and providers you have worked against, including open-weight ones, so recruiters can match your experience to their stack.
- Give every accuracy claim a baseline and a test set size, otherwise a hiring manager cannot tell a real gain from noise.
- Show retrieval work explicitly: chunking strategy, embedding model, reranking and how you measured grounding of the final answer.
- Include one bullet on safety work such as injection testing, refusal tuning or output filtering, since most teams now screen for it.
- Mention the cost and latency side of the job, because prompt choices decide the inference bill as much as they decide quality.