"Tell me about yourself" for software and AI engineers: a formula and 4 examples

It's the first question in almost every interview, and it sets the tone for the next 45 minutes. Yet most engineers either recite their resume line by line or say "I'm a passionate developer who loves learning" and stop.

Here's a simple structure that works for software engineers and AI engineers at every level, plus four sample answers.

What the interviewer actually wants

"Tell me about yourself" isn't small talk. In about a minute the interviewer is checking:

• Can you communicate clearly and briefly?
• Are you relevant to this role?
• What should they ask about next? Your answer sets the agenda for the follow-up questions, so mention the things you want to be asked about.

The formula: present, past, future

1. Present (20 to 30 seconds): who you are professionally right now. Your role or degree, what you work on, your main tech.
2. Past (30 to 40 seconds): one or two highlights that led here. A project, an internship, a result with a number.
3. Future (15 to 20 seconds): why this role and this company is the logical next step.

That's it. Aim for 150 to 220 words.

Example 1: fresher, software engineer

I'm a final-year Computer Science student at [college], and I enjoy backend development most, mainly Python and Node.js.

Over the last year I built a placement portal for our college that handles job postings and applications. About 1,200 students used it across three placement drives, and I worked on making the search fast enough to handle the traffic on drive days. I also did a two-month internship at a fintech startup, where I wrote APIs for their KYC flow and learned how code reviews and testing work in a real team.

I'm applying to this role because your team builds high-traffic backend systems, and that's exactly where I want to grow.

Example 2: fresher, AI engineer

I'm a final-year student in AI and Data Science, and I've spent most of this year building with large language models.

My main project is a question-answering assistant over our university's academic regulations. I built the retrieval pipeline, created a test set of 60 real student questions, and improved correct answers from about 55% to 80% by switching to hybrid search and adding a reranker. I also contributed a small fix to an open-source evaluation library.

I'm excited about this role because you're building LLM features that real customers use, and I want to learn how to evaluate and run them at scale.

Example 3: backend developer moving into AI

I'm a backend engineer with three years of experience at [company], where I work on the payments platform in Java and Python.

Last year I led a small project to add an internal assistant that answers support questions from our runbooks. That got me hooked on AI engineering. I built the retrieval and evaluation setup, and it now resolves about a third of internal support questions without a human. I've since completed [course or certification] and built two more LLM projects on my own.

I'm looking for a role where AI is the core of the product, and your team's work on [product] combines the backend reliability I know with the LLM work I want to do full-time.

Example 4: experienced AI or ML engineer

I'm a senior ML engineer at [company], where I lead a team of four building the recommendation and search features in our app.

Over the past two years I moved our search from keyword-only to hybrid semantic search, which improved click-through by around 12%, and I set up our offline evaluation pipeline so we could ship model changes weekly instead of monthly. Before that I spent two years as a data scientist working on fraud models.

I'm interested in this role because you're building agents that take real actions, and I want to work on the evaluation and safety side of that problem.

Replace the details with your own real numbers. Interviewers will ask about every claim, so never exaggerate.

Mistakes to avoid

• Reading out your resume. They have it. Pick highlights instead.
• Starting from school. Unless you're a fresher, start with what you do now.
• No numbers."Improved performance" is forgettable; "cut API latency by 40%" isn't.
• Going over two minutes. Leave room for follow-up questions.
• Ending with nothing. Always close with why this role.
• Personal details nobody asked for. Family, hometown and hobbies usually don't belong here.

How to practise in 10 minutes

1. Write your present, past and future points as bullet points, not a script.
2. Say it out loud with a timer. Cut until it fits in 90 seconds.
3. Record yourself once and listen for filler words.
4. Make a slightly different ending for each company you apply to.

Short on time? Paste your resume into our free Tell Me About Yourself generator for a first draft, then edit it so it sounds like you. For the behavioral questions that usually come next, see our STAR method guide.