AI Engineer resume example
By Bhagirath Sheela, founder of JobCatch ·
AI engineer is the newest title on this list, and most postings mean one thing: building products on large language models. Employers want people who can ship an LLM feature that is accurate, safe and affordable — retrieval, evaluation and cost control matter more than model theory.
What recruiters look for
- LLM features in production: retrieval (RAG), agents, tool use
- Evaluation: how you measured quality and caught regressions
- Cost, latency and safety: caching, guardrails, prompt-injection defence
- Solid software engineering in Python or TypeScript
Section order
With experience
- Summary
- Skills
- Experience
- Projects
- Education
- Certifications
As a fresher
- Summary
- Education
- Skills
- Projects
- Internships
- Certifications
Summary examples
Fresher
AI engineer with a B.Tech in computer science and two LLM projects in production use, including a RAG assistant for a college's academic rules used by 900 students.
Experienced
AI engineer with five years in software and two building LLM features. Shipped a support assistant that resolves 41% of tickets and cut per-answer cost by 70%.
Skills, spelled the way postings spell them
An applicant tracking system matches the words in the job posting, and it does not reliably treat two spellings as one skill. The left column is the form most postings use; the right, other spellings people type. Use the posting's own spelling for each application, and list only what you can discuss in an interview.
| Skill | Also written as |
|---|---|
| Large language models (LLMs) | LLM, LLMs, GenAI, Generative AI |
| Prompt engineering | — |
| Python | Python 3 |
| Natural language processing | NLP |
| Machine learning | ML |
| FastAPI | Fast API |
| REST APIs | REST, RESTful APIs, REST API |
| Docker | Containerisation, Containerization |
| AWS | Amazon Web Services |
| PostgreSQL | Postgres, PostgresSQL |
| TypeScript | TS |
| Git | Version control, GitHub, Bitbucket |
Also worth listing if you have them: Retrieval-augmented generation (RAG), Vector databases, LLM evaluation.
Bullet examples
Each bullet says what you did and what changed because of it. Change the numbers to your own; a recruiter will ask about every one.
- Shipped an LLM support assistant with retrieval over 6,000 help articles; it resolves 41% of tickets without an agent.
- Built an evaluation set of 800 real questions that runs on every prompt change and blocks regressions.
- Cut cost per answer by 70% with response caching and routing simple questions to a smaller model.
- Added prompt-injection checks and output filters after a red-team exercise found 12 failure cases.
- Built the document-ingestion pipeline that chunks, embeds and refreshes content nightly.
For freshers: projects and internships
- Built a RAG assistant over a college's academic rules, used by 900 students in its first term.
- Built a resume-to-job matching demo with embeddings and an evaluation set of 200 labelled pairs.
- Internship: wrote Python tools that an LLM agent calls to look up order status.
Mistakes to avoid
- Listing model names and prompt tricks with no shipped feature. Employers want something people used.
- No evaluation. Saying how you measured quality is what separates an AI engineer from a demo builder.
- Ignoring cost and safety. Both are now standard interview questions for LLM roles.
What an ATS reads from this sample
An applicant tracking system turns the PDF into plain text before anyone reads it. This is that text for the sample above, extracted by the same code as "What the ATS reads" in the app. Everything is in reading order, under the right heading, with the name and email intact — which is what a single-column template is for.
Ishaan Malhotra AI Engineer [email protected] | +91 98765 43210 | Bengaluru, Karnataka | linkedin.com/in/ishaanmalhotra Summary AI engineer with five years in software and two building LLM features. Shipped a support assistant that resolves 41% of tickets and cut per-answer cost by 70%. Technical skills Large language models (LLMs) · Prompt engineering · Python · Natural language processing · Machine learning · FastAPI · REST APIs · Docker · AWS · PostgreSQL · TypeScript · Git · Retrieval-augmented generation (RAG) · Vector databases · LLM evaluation Projects Rules assistant RAG assistant over a college's academic rules; 900 students used it in its first term. Experience AI Engineer, Helpdeck Software Apr 2024 – Present Bengaluru Shipped an LLM support assistant with retrieval over 6,000 help articles; it resolves 41% of tickets without an agent. Built an evaluation set of 800 real questions that runs on every prompt change and blocks regressions. Cut cost per answer by 70% with response caching and routing simple questions to a smaller model. Software Engineer, Invoxa Software Jul 2021 – Mar 2024 Bengaluru Added prompt-injection checks and output filters after a red-team exercise found 12 failure cases. Built the document-ingestion pipeline that chunks, embeds and refreshes content nightly. Education B.Tech, Computer Science 2017 – 2021 Manipal Institute of Technology · 8.5 CGPA Languages English, Hindi
Interview questions to prepare
The app's interview prep for this sample and a plain AI Engineer posting. It works from the resume and the posting only, and tells you how to prepare, never what to say.
Questions every interview has
- Tell me about yourself. Two minutes: what you do now (AI Engineer at Helpdeck Software), one result you are proud of, and why this role is next.
- Why do you want this job? Read their website and one recent piece of news before the call. Name something specific.
- Why are you leaving your current job? Say what you are moving towards. Do not criticise your employer.
- What is your notice period, and what salary are you expecting? Decide your number before the interview, so you are not deciding it on the call.
About the skills the job asks for
- Tell me about a time you used Python. Pick one real example: what the problem was, what you did, and what changed.
- Tell me about a time you used FastAPI. Pick one real example: what the problem was, what you did, and what changed.
- Tell me about a time you used Machine learning. Pick one real example: what the problem was, what you did, and what changed.
- Tell me about a time you used Natural language processing. Pick one real example: what the problem was, what you did, and what changed.
- Tell me about a time you used Large language models (LLMs). Pick one real example: what the problem was, what you did, and what changed.
- Tell me about a time you used Prompt engineering. Pick one real example: what the problem was, what you did, and what changed.
About what the resume claims
- You wrote: "Shipped an LLM support assistant with retrieval over 6,000 help articles; it resolves 41% of tickets without an agent." Expect three follow-ups: how exactly, what was your own part, and how you know it worked.
- You wrote: "Built an evaluation set of 800 real questions that runs on every prompt change and blocks regressions." Expect three follow-ups: how exactly, what was your own part, and how you know it worked.
- You wrote: "Cut cost per answer by 70% with response caching and routing simple questions to a smaller model." Expect three follow-ups: how exactly, what was your own part, and how you know it worked.
Questions to ask them
- What would a good first three months in this role look like?
- Who would I work with most closely?
- What are the next steps, and when should I expect to hear back?
Templates that suit this role
All of these are single-column and read cleanly by an applicant tracking system. Classic is free, with no watermark.
Questions
What should an AI engineer resume include in 2026?
Shipped LLM features, how you evaluated them, how you kept them affordable and safe, and the software engineering behind them. Model theory matters less than these for most product roles.
Should I write GenAI, LLM or AI on my resume?
Postings use all three. Write "large language models (LLMs)" and "generative AI" once each so searches match, then describe the actual work — retrieval, agents, evaluation.
Next: the AI Engineer cover letter the app drafts from this resume, and how to show Python, REST APIs, Docker on a resume.
More data & ai resume examples: Data Analyst · Business Analyst · Data Scientist · Data Engineer · Machine Learning Engineer · Power BI Developer · SQL Developer