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Prompt Engineer Resume Example

What the role is, a real Prompt Engineer resume example, and exactly what recruiters look for — then build your own in minutes.

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What is a Prompt Engineer?

A Prompt Engineer designs, tests, and optimises the prompts and context that steer large language models (LLMs) to produce accurate, safe, and useful outputs. They turn a fuzzy product goal into reliable model behaviour — through prompt design, retrieval, evaluation, and guardrails.

The role blends applied AI with product and linguistics. Day to day it involves crafting and versioning prompts, building retrieval-augmented generation (RAG) pipelines, running systematic evals, reducing hallucinations, and tuning cost and latency across model providers.

As companies ship LLM features across search, support, and workflows, the Prompt Engineer (often titled AI Engineer or LLM Engineer) has emerged as a fast-growing 2026 role — the person who makes generative AI dependable in production.

Key skills for a Prompt Engineer resume

  • Prompt design & versioning (few-shot, chain-of-thought, structured output)
  • Retrieval-augmented generation (RAG) & embeddings
  • LLM evaluation & benchmarking (evals, A/B tests)
  • Vector databases (Pinecone, Weaviate, pgvector)
  • LLM frameworks (LangChain, LlamaIndex) & function calling
  • Python & API integration across model providers
  • Guardrails, safety & hallucination reduction
  • Cost, latency & token optimisation

Prompt Engineer resume example

Lena Vermeer

Prompt Engineer / AI Engineer

Rotterdam, Netherlands

Summary

Prompt / AI Engineer with 4+ years building production LLM features across support, search, and internal tools. Combines rigorous evaluation with strong Python and RAG engineering to ship generative-AI products that are accurate, safe, and cost-efficient.

Experience

AI Engineer (Prompt Engineering) · Mollie

Jun 2023 – Present

  • Designed and shipped a RAG-based support assistant (LangChain + pgvector) that deflected 38% of tickets, with an eval suite guarding accuracy on every release.
  • Built a prompt-versioning and offline-eval workflow (golden sets + A/B tests) that cut hallucinations 55% and made releases measurable.
  • Reduced token cost 45% and p95 latency 50% via prompt compression, caching, and model routing across providers.
  • Added guardrails (structured output, validation, PII redaction) to meet security and compliance requirements.

Software Engineer, Applied AI · TomTom

Sep 2021 – May 2023

  • Built embedding-based semantic search over internal documentation used by 500+ engineers.
  • Integrated LLM function-calling into internal tools to automate structured data extraction.

Education

MSc Artificial Intelligence

Delft University of Technology (TU Delft) · 2019 – 2021

BSc Computer Science & Linguistics

Utrecht University · 2016 – 2019

Certifications

  • DeepLearning.AI — LangChain for LLM Application Development
  • DeepLearning.AI — Building Systems with the ChatGPT API

Skills

LLM: Prompt Design · RAG · Function Calling · Fine-tuning · Guardrails

Frameworks: LangChain · LlamaIndex · Hugging Face · OpenAI / Anthropic APIs

Retrieval: Embeddings · pgvector · Pinecone · Weaviate

Engineering: Python · FastAPI · Evals · A/B Testing

Use this as your starting point

How to write a Prompt Engineer resume that stands out

  • Show measurable quality gains — accuracy, hallucination rate, task success, or deflection — not just “wrote prompts”. Evals are the proof of the craft.
  • Demonstrate a systematic approach: prompt versioning, eval sets, and A/B testing. Reviewers want rigour, not vibes.
  • Name the stack — model providers, RAG framework, vector DB, and eval tooling. It signals real production experience.
  • Quantify cost and latency wins (e.g. “cut token cost 45%”, “halved p95 latency”) — LLM features live and die on unit economics.
  • Include shipped LLM features with users served; production impact beats prompt playgrounds.

Prompt Engineer resume — FAQ

What does a Prompt Engineer do?

A Prompt Engineer designs and optimises the prompts, context, and retrieval that guide large language models to produce accurate, safe, useful outputs. They build RAG pipelines, run evaluations, add guardrails, and tune cost and latency so LLM features work reliably in production.

What skills should a Prompt Engineer put on a resume?

Prompt design techniques (few-shot, chain-of-thought, structured output), retrieval-augmented generation and embeddings, LLM evaluation, vector databases, LLM frameworks (LangChain/LlamaIndex), Python and API integration, and safety/guardrails. Cost and latency optimisation is a strong plus.

Is prompt engineering a real job?

Yes — though the title varies (Prompt Engineer, AI Engineer, LLM Engineer). The core work is making generative AI reliable in production: prompt and RAG design, evaluation, guardrails, and cost/latency tuning. It combines applied AI, software, and product judgement.

What should a Prompt Engineer resume include?

Lead with a summary that frames you as someone who ships reliable LLM features. Show shipped features with measurable quality, cost, and latency impact, your eval methodology, and the exact stack (model providers, RAG framework, vector DB). Keep it ATS-safe with clean structure and real text.

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