Live technical interviews built for software engineers

Practice software engineering mock interviews with AI

Speak naturally, solve the problem in the right technical workspace, defend your decisions under realistic follow-ups, and review an evidence-based report after the interview.

Coding / DSA · System Design · Object-Oriented Design / LLD · AI-Assisted Coding

What it is
EngMock (engmock.com) is an AI mock interview platform for software engineers: a live voice interviewer runs the interview on a whiteboard or in a coding workspace, asks follow-ups, and writes a scored report from the evidence in the session.
The library
100 mock interviews across four interview tracks: 43 system design, 25 coding (DSA), 26 object-oriented design (OOD) and 6 AI-assisted coding.
Start free
New accounts get two Free Credits: each covers one complete live interview on a Free Credit eligible scenario (Find a Pair Matching a Target or Design a URL Shortener), with its full report.
Pricing
After that, one-time interview credit packs from $10, or the Unlimited plan at US$9.99 a month on your own Gemini API key.

The technical interview loop

Practice the round you are actually preparing for

A software engineer mock interview should reproduce the work and communication expected in that round, not reuse one generic chat interface for every format.

Focused preparation paths

Practice the exact role, level, or systems specialty

Each guide combines a timed session plan, targeted scenarios, a role-specific scorecard, FAQ answers, and automatic links back to the practice library.

Role preparation

Senior Software Engineer Mock Interview

Practice the shift from solving a contained problem to owning ambiguous requirements, technical risk, operational trade-offs, and the clarity of the team around you.

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Role preparation

Backend Engineer Mock Interview

Rehearse the work behind a reliable service: contract design, state transitions, concurrency control, storage choices, failure handling, and production diagnosis.

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Role preparation

Frontend System Design Interview

Design the browser application as a production system: user journeys, component boundaries, state ownership, network behavior, performance budgets, accessibility, and safe delivery.

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Role preparation

Machine Learning Engineer Mock Interview

Connect model quality to a working product: define the objective, prevent leakage, design evaluation, serve predictions, monitor drift, and make failures safe.

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Role preparation

Staff Engineer System Design Interview

Practice architecture at organizational scale: choose the right problem, define boundaries, manage migration and risk, and create a strategy multiple teams can execute.

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Frontier AI company

OpenAI Coding Interview Preparation

Build a coding practice loop around clear reasoning, correct implementation, validation, and deeper follow-ups—without relying on leaked or claimed official questions.

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Frontier AI company

Anthropic System Design Interview Preparation

Practice designing reliable AI products and infrastructure with explicit evaluation, safety boundaries, failure containment, observability, and human control.

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Frontier AI company

Google DeepMind Research Engineer Preparation

Practice the bridge between research ideas and dependable experiments: algorithms, measurement, reproducibility, scalable training, performance, and clear technical communication.

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Systems specialty

AI Infrastructure Interview Questions

Practice the systems behind modern AI workloads: accelerator scheduling, distributed training, inference serving, model and data movement, reliability, observability, and cost.

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Systems specialty

Distributed Systems Mock Interview

Practice reasoning when messages duplicate, machines fail, clocks disagree, capacity shifts, and the system still has to protect user-visible invariants.

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Interview format

Meta AI-Assisted Coding Interview

Practice the coding round where you are expected to use an AI assistant: read unfamiliar code, hand the assistant small tasks, check what it writes, and stay in charge of the solution.

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What makes the mock realistic

Your reasoning and workspace become the evidence

EngMock evaluates what you clarified, said, drew, coded, tested, and changed during the recorded session. The report does not invent a score from a final answer alone.

Live voice

Explain naturally while the interviewer probes missing assumptions and weak trade-offs.

Purpose-built workspace

Use a whiteboard, a single-file coding editor, a multi-file workspace, or your own VS Code.

Interview pressure

Practice inside a 45- or 60-minute session with an explicit target level.

Evidence-based review

Replay the interview and connect feedback to the exact moments that produced it.

Top tech and frontier AI labs

Prepare for modern engineering teams, from big tech to frontier AI labs

Company guides combine current official process information with clearly labelled independent practice. They never present company-style exercises as official or leaked questions.

AI engineering practice

AI and ML systems scenarios

Run your next software engineer mock interview

Choose a technical round, set your target level, speak your reasoning aloud, and review the evidence after the session.

Start a free mock interview