Mobile Engineer (Remote)

About Kinterview: Kinterview (kinterview.cc) is a real-time AI interview copilot. It listens to interviewers' questions and streams tailored answers to a private window, in 23 languages, on Zoom, Google Meet, and Microsoft Teams. We're a remote-first team on a mission to end interview anxiety for job seekers everywhere.

Location: Remote, work from anywhere (some overlap with UTC+8 mornings preferred).

What we offer: Competitive salary; fully remote and async-first; annual team offsite; learning & equipment budget; early-stage equity.

How to apply: Email your resume and a short note to [email protected] with the role title in the subject line.

01What you'll do

• Bring Kinterview to iOS and Android: real-time transcription and answer streaming on the go.
• Nail system-audio capture and low-latency UI on both platforms.
• Ship to the App Store and Play Store on a regular cadence.

02What you bring

• 3+ years shipping production mobile apps (Swift/Kotlin, or React Native/Flutter with native depth).
• Experience with background audio processing and platform permission models.
• Strong instincts for mobile UX constraints.

03Nice to have

• On-device ML or streaming inference experience.

04About the product you'll be working on

Kinterview is a real-time AI interview copilot. When a candidate is in a live interview on Zoom, Google Meet, or Microsoft Teams, Kinterview listens to the interviewer's questions and streams tailored answers to a private window, in 23 languages.

Interviews are high-stakes moments, and the product exists to support candidates in that moment: the transcription has to keep up, the answers have to fit the question being asked and the candidate's own background, and the interface has to stay calm and out of the way while the candidate is under pressure. Every part of the product serves that moment.

05How the team works

We are a remote-first company and a small team (1-10 people), hiring remotely worldwide. We work async-first and in writing across time zones, with some overlap with UTC+8 mornings preferred so we can meet live when it matters. There is no handoff theater: the people who design and build a feature are the people who hear from users about it, and everyone owns their work end to end, from idea to shipped, measured, and iterated. If you like small teams where your work reaches users directly, you will fit in here.

06What we offer

Competitive salary, fully remote and async-first work, an annual team offsite, a learning and equipment budget, and early-stage equity.

07How to apply

Email your resume and a short note to [email protected] with the role title in the subject line. Tell us briefly why this role and what you have built or done that is most relevant.

More on this role: this role takes Kinterview out of the desktop and into the candidate's pocket, and the interview does not pause for the phone to catch up. You will bring Kinterview to iOS and Android, with real-time transcription and answer streaming on the go, the same live moment as on desktop, in a form the candidate can carry into the room where the interview happens.

That means nailing system-audio capture and low-latency UI on both platforms: capturing the interviewer's audio cleanly enough to transcribe it, and showing the tailored answer quickly enough, and calmly enough, that it helps rather than distracts while the candidate is under pressure. You will ship to the App Store and Play Store on a regular cadence, so releases become routine rather than events, and each release carries what you have learned from the last one.

That work draws on three or more years shipping production mobile apps in Swift or Kotlin, or in React Native or Flutter with real native depth, on experience with background audio processing and platform permission models, the parts of a phone that decide whether an app can keep listening and keep working when it is not on screen, and on strong instincts for mobile UX constraints, for what fits on a small screen in a stressful moment and what does not.

On-device machine learning or streaming inference experience will help where the mobile app has to do more of the work itself, close to the audio, rather than waiting on a round trip.