Softway Careers | AI Applied Engineer

About the Role

AI-first by instinct. Product-minded by default.

We have an opening in our team — and we're using it to raise the bar. We're looking for someone who's already adapted to solving problems with AI: a builder who reaches for AI before they reach for a wireframe, who thinks in prompts and agents as fluently as in components, and who treats AI as the lever, not the buzzword.

The base craft we're hiring for is React Native. But we're not boxed in by a single technology. We're a build-anywhere, learn-anywhere team — happy to move across frontend, backend, or wherever the problem leads. The best people here don't say "that's not my stack." They say "let me figure it out."

This is an in-person role. We believe the best work, the best decisions, and the best teams happen in the same room. Face-to-face collaboration isn't a footnote here — it's how we actually operate.

What You'll Do

Real work. Real ownership. Real pace.

Build AI-powered mobile features and tools for Softway's client engagements — from early prototype to shipped product, in React Native.
Integrate LLM APIs, agents, and intelligent workflows into real applications that real people use on the floor, in the office, and in the field.
Own features end-to-end — not just the screen. You'll touch APIs, backend logic, cloud services, and data layers as the problem demands.
Think in prompts, agents, and evals — and bring that thinking into every build, not just when someone asks for "an AI feature."
Ship in small, fast loops. Question the brief. Care how the thing feels in someone's hand.
Collaborate across Softway's multidisciplinary team — strategy, culture, creative — to make sure what you build is grounded in real human outcomes.
Stay ahead of what's emerging in the AI-native stack and bring it back. We expect you to be reading, building, and sharing constantly.

What We're Looking For

Show us what you've shipped — not just what you know.

We're not hiring for a checklist. But the right person will read this and recognise themselves:

You've shipped real things with AI — not just weekend experiments. Products that worked, problems that got solved. Show us what you built.
Around 2–5 years of React Native experience, with strong roots in TypeScript, JavaScript, and React. You're fluent, not just familiar.
You're comfortable across the stack — Node.js, APIs, cloud services. You can own a feature end-to-end, not just the screen.
You think in agents, prompts, and evals. You treat AI as a collaborator — and you know when not to use it, which matters just as much.
You have a product brain. You question the brief. You care how the thing feels in someone's hand. You ship in small, fast loops and iterate from there.
You communicate what you built and why — clearly, without jargon, to people who aren't engineers. At Softway, that matters every day.
You use AI in your own workflow because you can't imagine working without it — not because someone told you to.

We'll especially notice if you've...

Built with agents, MCPs, or custom evals in a real product context.
Integrated LLM APIs into something that shipped — not just a demo.
Open-sourced something, or shipped 0→1 at a startup.
Got a side project, a repo, a demo, or a write-up you'd want to show us. A link tells us more than a line on a resume.

The Challenge

A real problem. Build something that actually helps.

This is the same challenge every AI Applied Engineer candidate receives. There's no single right answer. We're evaluating how you think, what you build, how you use AI — and whether you can hold the human in mind alongside the technical.

The Scenario

A manufacturing facility has 5 HVAC systems streaming real-time sensor data — temperature, airflow, vibration, pressure — and a maintenance team that has completely stopped trusting their alert system.

90% of alerts are false alarms. Two costly equipment failures happened last quarter because real problems got buried in noise. The team has developed "alert fatigue" — they've started silencing notifications. A previous threshold-based system made it worse. The team specifically asked for something smarter. Something that actually understands what's happening. The sensor dataset is provided — some of it messy, some missing, some deceptive. That's intentional.

Download Sensor Dataset →

Why This Matters

In manufacturing environments, unplanned equipment downtime costs $5,000–$15,000 per hour. A team of 12 technicians covers 200+ HVAC units across 3 shifts. They're on the floor — not at desks. The solution needs to fit in their pocket and tell them exactly where to go and why. This is a real problem pattern across our industrial clients. What you build here could directly inform how we approach similar engagements.

Build a React Native mobile app

Using the provided sensor dataset, build a working React Native app (Expo is fine) that uses AI to help technicians know what needs their attention and why. The experience, the logic, the interface — that's on you. It doesn't need to be polished. It needs to work and show genuine thinking.

Write a README that shows your thinking

Cover: your approach to the problem, how you used AI in building the solution, the trade-offs you made, and what you'd do differently with more time. This is as important as the code.

Record a short walkthrough video

2–3 minutes. Walk us through what you built and why. Not a demo script — tell us what you were thinking. What worked. What didn't. What you'd change.

What to Submit

→ A GitHub repo with your React Native app and README

→ A link to your walkthrough video (Loom, YouTube unlisted, or similar)

→ Your resume — we evaluate both together

A note on AI use: Use AI actively throughout — in your code, your thinking, your README. We expect it. What we're evaluating is your judgment: how you direct AI, how you verify its outputs, and whether what you ship is genuinely useful to a real person on a factory floor. Using AI well is a signal. Using it without thinking is just noise.

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Submission Deadline

10th May 2025

AI AppliedEngineer