Experience · Internship

Software Engineer Intern

Aude.ai

Joined as a software engineer intern on the product team, working across a Next.js frontend and a Node and Express backend. After the first month I was given the chance to design and build an internal diagnostics application, which became the main focus of the role.

Period
Location
Remote
Work mode
Remote

About the role

I joined Aude.ai as a software engineer intern on the product team. The product is a Next.js frontend backed by a Node and Express service using Redis, and the first month was spent working in it directly — exploring the codebase, then finding and fixing bugs, mostly on the UI.

On the strength of that first month I was given the opportunity to design and build an internal diagnostics application for the engineering team. That became the main body of the internship, alongside continuing product work and UX discussions.

What I worked on

  1. 01Improvement

    Product work and UI bug fixes

    Started in the existing Aude product — a Next.js frontend with a Node and Express backend using Redis — exploring the codebase and fixing bugs across it, mostly on the UI. This first month built up the familiarity with the product's data flows that the diagnostics work later depended on.

    Next.jsReactNode.jsExpressRedis
  2. 02Feature

    Internal diagnostics dashboard

    After the first month I was given the chance to design and build an internal diagnostics application, which I built as a Next.js monolith. It talks directly to the database, checks whether the main app is generating correct data for every client, and shows the state of all of them in one dashboard. The interface is built for the engineers who debug it: what is not working is visible at a glance, an investigation can be deep-linked and shared as a URL, and a user's-eye view shows the UI as the user sees it next to the API response behind it.

    Next.jsReact
    Read the Aude Diagnostics case study
  3. 03Infrastructure

    Deployment behind the existing single sign-on

    Containerised the diagnostics app with Docker and deployed it on AWS, serving it from the same origin as the main application so it reuses the existing single sign-on instead of introducing a second authentication system. Access is further restricted to authorized members of the engineering team.

    DockerAWSNext.js
    Read the Aude Diagnostics case study
  4. 04Improvement

    Skeleton loading states

    Took part in UX improvement discussions and proposed skeleton loading for the app, which had no loading view. The proposal was approved, I implemented it, and it is now in production.

    Next.jsReact

Recommendation

Saikiran has been a phenomenal asset to our engineering team at Aude.ai. As a Software Engineer Intern, he stepped up to take end-to-end ownership of core workflows, designing a full-stack diagnostic web application and successfully deploying it on AWS. Beyond his backend and data pipeline work, Saikiran possesses a strong product mindset. He actively contributed to UX discussions, personally engineering performance enhancements like skeleton loading that made it directly into production. He even went above and beyond to learn DaVinci Resolve to build our high-quality product teaser video. He has a rare combination of technical autonomy, rapid learning velocity, and a growth mindset. I highly recommend Saikiran to any high-velocity team looking for a sharp, versatile full-stack developer

Keith JiaCEO and Founder, Aude.aiManaged Saikiran directlyView on LinkedIn

Highlights

  • Worked across the product — a Next.js frontend with a Node and Express backend using Redis — starting with UI bug fixes before taking on larger work.
  • Was given ownership of an internal diagnostics application after the first month, and built it as a Next.js monolith that verifies per-client data integrity for the main product.
  • Designed the dashboard for troubleshooting, with failures visible at a glance, deep-linkable investigations, and a user's-eye UI view paired with its API response.
  • Containerised it with Docker and deployed it on AWS so it reuses the main product's existing single sign-on, with access restricted to authorized members of the engineering team.
  • Proposed and shipped skeleton loading states, now in production.

Skills and technologies

Next.jsReactNode.jsExpressRedisDockerAWS

What I learned

  • How to design an internal tool around a debugging workflow rather than around the data model.
  • That an authentication constraint can often be resolved through deployment topology rather than by adding a second identity system.
  • That a well-argued UX proposal can go from discussion to production as an intern.
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