Artificial Intelligence & ML
ATS Resume Checker for AI Engineers
Get your resume ATS score in under 30 seconds. See exactly which AI Engineer keywords are missing and fix them before you apply.
ATS Score Benchmark — AI Engineer Roles
Average AI Engineer resume scores 55 — most get filtered before a human sees them.
How ATS Screens AI Engineer Resumes
AI Engineer is the fastest-growing role in 2026, with posting volume up 340% YoY globally. Greenhouse and Ashby at AI-first companies filter specifically for LLM orchestration frameworks (LangChain, LlamaIndex), named vector databases, and RAG architecture — not just "AI experience." Evaluation frameworks (RAGAS, PromptFoo) and production deployment experience are strong differentiators as the market matures from experimentation to production systems.
Top ATS Keywords for AI Engineer Resumes
These are the highest-weighted keywords ATS looks for in AI Engineer applications. Missing even 3–5 of these can drop your score below the recruiter's filter threshold.
Resume Bullet Examples — Weak vs. Strong
See how the same experience reads to ATS before and after optimisation.
"Built an AI chatbot using OpenAI APIs for customer queries."
"Designed and deployed a RAG-based enterprise knowledge assistant using LangChain, OpenAI GPT-4o, and Pinecone (2M+ document chunks indexed); achieved 87% answer accuracy on internal RAGAS benchmark while reducing customer support ticket volume by 34%, saving ~$280K/year."
"Fine-tuned LLMs for different use cases."
"Fine-tuned Llama 3.1 8B on 14K proprietary legal contracts using QLoRA (Python, HuggingFace PEFT); achieved 91% clause extraction accuracy vs. 64% GPT-4o zero-shot baseline, reducing manual contract review time by 70% for a 50-lawyer team."
6 Common AI Engineer Resume Mistakes
These are the specific patterns that cause AI Engineer resumes to fail ATS — and lose to less-experienced candidates.
- 1Listing "AI experience" without specifying LLM vs. classical ML vs. deep learning — these are scored as distinct, non-interchangeable skills
- 2No RAG architecture context — Retrieval-Augmented Generation is the #1 most demanded AI engineering pattern in 2026 JDs
- 3Missing vector database name — Pinecone, Chroma, or Weaviate must be explicit; "vector search" alone is insufficient for ATS filters
- 4Prompt engineering without evaluation — RAGAS or LLM-as-judge evaluation frameworks separate engineers from hobbyists
- 5No production deployment signal — "built a chatbot" vs "deployed an AI agent serving 50K daily users at 99.9% uptime" are worlds apart
- 6Leaving out LLM cost optimisation — token budget management, caching, and model selection are rising filter keywords as companies mature past experimentation
Frequently Asked Questions
What ATS score do I need as a AI Engineer?
A score of 73+ is considered strong for AI Engineer roles. Most candidates score around 55, meaning they are filtered before a recruiter reads their resume. Check yours free in 30 seconds.
Which ATS systems screen AI Engineer applicants?
The most common ATS platforms for AI Engineer hiring are Greenhouse, Lever, Ashby, Workday, SmartRecruiters. Our checker simulates how these systems score your resume against a job description.
Is this resume checker free?
Yes — your first ATS score is completely free with no signup required. Upload your resume (PDF or DOCX) and a job description, and get your score in under 30 seconds.
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