AI engineer resume: what to put on it
Start with work experience, then live projects, then skills and education, because recruiters scan for whether you've worked on problems like theirs. Write each AI project as one short entry: the problem, what you built, one measured result and a link. Mention tools inside those entries, not in a long keyword list, and only write what you can explain in depth, because every line is an interview question you've agreed to answer.
Why AI resumes get rejected
Many resumes now list MCP, A2A, RAG, LangGraph and fine-tuning, and the candidate can't explain any of them when asked. Interviewers notice quickly, and one acronym you can't explain makes them doubt the rest.
Order
| Section | What goes in it |
|---|---|
| Work experience | Problems you solved, with results |
| Leadership experience | Teams or projects you led, if any |
| Live projects | AI projects with links, most relevant first |
| Skills | Grouped, and only ones you've used |
| Education and certifications | Short, at the end |
Recruiters read the top first and scan for key points, so the most relevant experience goes first.
A project entry that works
The numbers here are placeholders for your own:
Policy assistant for a 400-page HR handbook. Hybrid retrieval (BM25 + embeddings) with
reranking, citations and abstention. Recall@5 from 0.71 to 0.89 after structure-aware
chunking. Deployed on Cloud Run, 120 weekly users. github.com/you/policy-assistant
Use your real numbers. If you didn't measure something, don't put a number on it.
Tools in context
"LangGraph" in a skills list says nothing. "Built a code-fixing agent with LangGraph that loops until tests pass, with a step limit and a sandbox" tells the interviewer what you used it for, and gives them a good question to ask.
Tailor it
Research the problems a company is solving and put your most relevant project first. If you know a domain like finance, apply to companies building AI for that domain, because your domain knowledge is part of what they're hiring.
Write it yourself
Use AI to get ideas or check wording, but write the resume yourself, so the language is yours when you explain it in the interview.
Certifications
Cloud certifications help for engineering roles. Most other certifications add little, so put them at the end and let the projects carry the resume.
Check before you send
- Can you explain every term on it in two sentences?
- Does each project have a link that works?
- Is every number something you measured?
- Is the most relevant project first for this company?
From the floor
In a personal branding and portfolio session, I shared the resume flow I recommend: work experience first, then leadership experience, then live projects, then hard and soft skills, then education, because a recruiter first wants to see that you've worked on problems similar to theirs, and I asked builders to write their resumes themselves, using ChatGPT only for ideas.
When I coach senior engineers for architect interviews, we go through the terms on their resume one by one, because even a director round can ask "what exactly is MCP and why would we use it?", and if you can't answer simply, either learn it properly or take it off.
Related
- AI engineer portfolio
- AI system design interview
- Backend to AI engineering
- Freelancing and consulting