Hire IoT Developers for Devices Already in Your Customers' Hands

When you hire IoT developers through Cortance, we look for work done after a device shipped: over-the-air updates, device state in the cloud, fleet migrations. As of October 2026, 30 engineers in our network have connected-device projects in their write-ups, from wearables and EV chargers to sensor fleets on MQTT.

A connected product changes hands on the day it ships. From then on, every firmware change travels over the air to a customer's home, a warehouse, or a clinic. So we match on engineers who have changed hardware they could no longer reach with a cable.

What goes wrong after a connected device ships?

The first failure is a disagreement about state. An app shows a lock as closed because the cloud recorded the command, while the lock never received it during a dropped connection. An IoT developer keeps the state the cloud wants apart from the state the device last reported, and shows the user which one they are looking at.

The second failure is an update that reaches hardware nobody tested. A firmware image that works on this year's board can stop an older revision from booting. A device that no longer boots needs a technician visit, not a patch. The third is the gap when the network drops: offline readings need timestamps and a buffer, or the dashboard fills with holes that look like outages. When we match an IoT developer, we look for these three moments in their project history, not for a list of protocols.

Three device fleets our IoT engineers changed in the field

Serhii P. worked on moving a computer and conference-hub manufacturer's devices from a legacy management platform to a new microservices platform. He built the migration service that sent MQTT commands to each device to update its software and register it on the new platform. The team moved 95% of the devices across.

Ivan Sh. kept the iOS app of a wireless audio product compatible with older hardware while shipping over-the-air firmware updates for chips from STMicroelectronics, Nordic, Atmel and Qualcomm. Four chip families meant four update paths to check before anything reached a customer.

Yuliia K. built the Java backend for DreamCub, a connected teddy bear that reports a child's sleep and routines to parents. She handled device-to-cloud messaging over MQTT and kept each toy's state in AWS IoT Core Device Shadow. The backend knows what the toy last reported, even while it is offline.

Where should an AI model act on sensor data, and where should a rule decide?

AI earns its place in IoT where a signal is too subtle for a fixed threshold. Ruslan B. built models that tell healthy bearings from failing ones by their vibration, in a predictive maintenance study with Kharkiv Polytechnic Institute. Michael Y. led a team whose reinforcement learning controller ran the climate of a working lettuce greenhouse in the Autonomous Greenhouse Challenge.

The judgment we look for is where the model stops. A model can flag a bearing or propose a climate setting. The device still needs a fallback rule for when the network is down, or the model is wrong, because the action is physical. AI coding assistants speed up packet parsers and dashboard screens, yet only a test against the hardware shows whether the bytes are right.

That line matters most in automation, which makes up a growing share of the work clients bring to Cortance. Emmanuel O. built the web control for restaurant robots that, by his account, took over 80% of waiter work at a university cafe in Nagoya.

Tell us what is already in the field

Send us three facts: how many devices are deployed or planned, how they connect (Bluetooth through a phone, Wi-Fi or cellular) and how updates reach them today. We use them to match an engineer who has worked on the same layer. Firmware on the microcontroller and board design are a separate hire, covered by our embedded engineers. Matched profiles arrive within 30 minutes. The engineer you choose can start within 2 days at a typical rate of $30-45 an hour.