06 / AI-NATIVE PRODUCT AND SOFTWARE ENGINEERING
AI-Native Fullstack Engineer
Connect a promising capability to a product people can use.
STEP INSIDE THE WORK
AN ILLUSTRATIVE PROJECTFollow the click all the way to the outcome.
A team needs to upload documents and ask questions. How do you make that a complete, dependable product flow?
YOUR MOVE / 01
Map the complete user journey.
Follow upload, processing, question, response and source inspection. Define what the interface, application API and database each need to do, including failures.
WHAT YOU MAKE VISIBLE
A complete user flow
Clear API boundaries
Loading and error behaviour
Think from first principles.
Make your reasoning visible.
01 / YOUR MISSION
Build the product. Understand every layer that makes it work.
An AI capability becomes useful when a person can act on it through a dependable product. That takes an interface, application logic, data, permissions and good decisions when something fails. At devx, you will build across those layers and use AI throughout your own engineering workflow. Bring the instinct to make things, the patience to trace a bug and the judgment to question generated code. Start with strength in one layer and grow towards an end-to-end contribution.
The application around the AI capability: user experience, backend services, persistence and integration. You work with AI engineers on model behaviour and with cloud engineers on deployment and reliability.
We reimagine customer interactions, business operations and enterprise architecture around AI. You bring fresh questions. Experienced practitioners bring context and judgment. The work connects both to a real customer outcome.
02 / WHAT YOU WILL WORK ON
Make your curiosity
useful.
Build complete product slices
Implement a bounded user journey across the interface, backend API and database. Use the project’s stack, agree contracts between layers and keep the design understandable enough for another engineer to extend.
Make AI part of how you engineer
Use approved coding assistants or agents to explore code, draft implementations, generate test ideas and investigate errors. Give them clear context, inspect the diff, run meaningful checks and be able to explain the result. You are responsible for the code you submit.
Integrate useful AI behaviour
Connect approved model or agent services through the backend. Handle structured responses, streaming where useful, timeouts and service limits. Work with AI engineers on retrieval and evaluation, and make the user’s fallback or next action clear.
Protect data and actions
Implement authentication and server-side authorization, validate inputs and keep credentials out of the browser. Check document and tenant access before retrieval or actions. Treat model output as untrusted input; consequential actions need explicit validation and the appropriate confirmation.
Make the experience usable
Build responsive, keyboard-accessible flows with clear loading, empty, success and error states. Help users inspect supporting information, correct inputs and recover from failures. Use feedback to improve the complete task.
Ship something maintainable
Write tests around important behaviour and service boundaries, review code with the team, and contribute useful logs and deployment notes. Debug across the stack and explain what a change improves, what it risks and how to roll it back.
What good work looks like
- A complete user flow that works across the interface, service and data layers.
- Evidence that important permissions, errors and service failures behave as intended.
- A reviewed change you can explain, test and maintain, including any AI-generated parts.
Use AI across understanding, implementation, testing and documentation. Break work into reviewable steps, verify generated dependencies and APIs, protect customer information, and judge progress by working behaviour rather than the amount of code generated.
03 / YOUR STARTING POINT
Bring a foundation.
Build the range.
Coursework, personal projects, research and student initiatives all count. Previous full-time experience is not required.
- Programming fundamentals, common data structures and the ability to debug code you did not write.
- A working understanding of HTML, CSS, JavaScript or TypeScript, HTTP and APIs, demonstrated through a small application.
- Basic backend and relational-database concepts, including validation, queries and why users need different access permissions.
- A project you can explain and extend. Strength in frontend or backend is a valid starting point if you are willing to learn the other layer.
Useful exposure
React or a comparable UI framework; Node.js, Python or another backend stack; SQL, Git, tests and an AI-assisted coding workflow. You do not need to know every framework or train models to apply.
04 / HOW YOUR OWNERSHIP GROWS
Learn in the work.
Grow through the feedback.
Start with a reviewed feature or integration in the layer where you have a foundation. Expand into a complete product slice, including API boundaries, tests, permissions and deployment behaviour. Grow towards end-to-end product engineering by learning when AI accelerates the work and when you need to investigate or design the solution yourself.
Explore
Understand the problem and ask useful questions.
Build
Make a defined contribution and learn through review.
Own
Take on broader responsibility as your readiness grows.
05 / THE DEVX CULTURE
The principles
show up in the work.
Understand what the customer is trying to change. Ask the extra question, surface the real obstacle and connect your work to their goals.
A feature shipped, but the workflow is still slow. Stay with the problem and find out why.
Client obsession. Understand what the customer is trying to change. Ask the extra question, surface the real obstacle and connect your work to their goals.
AI-native everything. Use AI to improve how you research, build, analyse and document. Understand its limits, verify the output and handle customer information responsibly.
Hire and train exceptional talent. We bring young talent and experienced practitioners together. Bring ambition, seek direct feedback and put new understanding into practice.
Document to scale. Write down the decision, its context and what you learned. Make your work understandable enough for someone else to continue, question or improve it.
Only ever be honest. Flag risk while there is time to act. Separate what you know from what you assume. Give clear feedback and make uncertainty visible.
06 / START A CONVERSATION
Show us the way
you think.
Share a résumé and one application, repository or project walkthrough. Explain the user problem, architecture, your contribution, an important bug and your checks. If you used AI, show what it helped with and how you validated its output.
Join through an internship with the opportunity to convert to a full-time role. The hiring team will share internship duration, work arrangements, campus eligibility and conversion criteria during recruitment.
An illustrative project
A customer team needs to upload documents, ask questions and inspect supporting sources. You could own a small application flow: upload status, an authorized API, persisted conversations and a usable error state. Test that one user's documents cannot be accessed by another, and that a model timeout produces a recoverable experience.