AI Engineer resume skills and keywords
In 834 AI Engineer job postings from 515 employers analysed on October 23, 2026, the most requested skills are LLMs (79 %), Python (71 %), APIs (48 %), Communication (45 %) and RAG (43 %). Of the top 40 skills, 35 are hard skills, tools or certifications and 5 are soft skills.
Download the full list as a CSV or check your own resume against a posting with the free keyword scanner.
Top 40 skills in AI Engineer job postings
| Skill | Share of postings | Type |
|---|---|---|
| LLMs | 79 % | Tool |
| Python | 71 % | Tool |
| APIs | 48 % | Hard skill |
| Communication | 45 % | Soft skill |
| RAG | 43 % | Tool |
| AWS | 36 % | Tool |
| TypeScript | 27 % | Tool |
| Generative AI | 26 % | Tool |
| Machine learning | 26 % | Hard skill |
| CI/CD | 25 % | Tool |
| Collaboration | 24 % | Soft skill |
| Azure | 24 % | Tool |
| Mentoring | 23 % | Soft skill |
| Prompt engineering | 23 % | Hard skill |
| GCP | 23 % | Tool |
| Leadership | 23 % | Soft skill |
| LangChain | 22 % | Tool |
| Tool use | 20 % | Tool |
| Problem Solving | 19 % | Soft skill |
| Data pipelines | 18 % | Hard skill |
| Guardrails | 18 % | Hard skill |
| Kubernetes | 18 % | Tool |
| Data Science | 17 % | Hard skill |
| Docker | 17 % | Tool |
| Evaluation frameworks | 16 % | Tool |
| Experimentation | 16 % | Hard skill |
| PyTorch | 15 % | Tool |
| Git | 14 % | Tool |
| Cloud Platforms | 14 % | Tool |
| SQL | 14 % | Tool |
| System design | 14 % | Hard skill |
| Machine Learning Operations | 13 % | Hard skill |
| AI Tools | 13 % | Tool |
| Software development | 13 % | Hard skill |
| Code review | 13 % | Hard skill |
| React | 12 % | Tool |
| Distributed systems | 12 % | Hard skill |
| Artificial Intelligence | 11 % | Hard skill |
| Debugging | 10 % | Hard skill |
| Go | 10 % | Tool |
Hard skills vs soft skills vs tools and certifications
Hard skills (14)
- APIs 48 %
- Machine learning 26 %
- Prompt engineering 23 %
- Data pipelines 18 %
- Guardrails 18 %
- Data Science 17 %
- Experimentation 16 %
- System design 14 %
- Machine Learning Operations 13 %
- Software development 13 %
- Code review 13 %
- Distributed systems 12 %
- Artificial Intelligence 11 %
- Debugging 10 %
Soft skills (5)
- Communication 45 %
- Collaboration 24 %
- Mentoring 23 %
- Leadership 23 %
- Problem Solving 19 %
Tools and software (21)
- LLMs 79 %
- Python 71 %
- RAG 43 %
- AWS 36 %
- TypeScript 27 %
- Generative AI 26 %
- CI/CD 25 %
- Azure 24 %
- GCP 23 %
- LangChain 22 %
- Tool use 20 %
- Kubernetes 18 %
- Docker 17 %
- Evaluation frameworks 16 %
- PyTorch 15 %
- Git 14 %
- Cloud Platforms 14 %
- SQL 14 %
- AI Tools 13 %
- React 12 %
- Go 10 %
Keyword phrases recruiters use
Multi-word phrases that recur across these ai engineer postings, with the share of postings that use each one.
How to use this on your resume
Treat the table as a checklist, not a script. Put the skills you genuinely have in your skills section, using the same wording as the posting, and back the top ones with a bullet that shows the result.
Each job posting differs from the average, so compare your resume with the actual ad: paste it into the resume keyword scanner to see which terms you already have and which are missing. The ATS keywords guide explains where to place them so applicant tracking systems read them.
Skip any skill you cannot talk about in an interview; a keyword that falls apart under one question costs more than it gains. For a full layout with these skills in context, see the AI Engineer resume example. Then prepare for the AI Engineer interview questions that test them.
Build a ai engineer resume with these skills
Start in the editor, tailor your bullets to the job you want and download an ATS-friendly resume.