Edge Computing Engineers Who Think in Firmware, Cloud, and Everything Between

The edge computing talent gap demands engineers who can work across the entire stack — from resource-constrained MCUs to cloud-native backends. needCode deploys pre-integrated teams from Central Europe with the rare hybrid expertise your edge projects require.

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Edge computing projects fail because the talent doesn't exist in one person

Global spending on edge computing is projected to reach $380 billion by 2028. Over 75% of enterprise data is now processed at the edge rather than in the cloud. Every industry – manufacturing, logistics, healthcare, agriculture, smart buildings, automotive – is racing to deploy intelligence closer to the data source. Yet the engineering talent required to deliver these systems sits at the intersection of three disciplines that rarely overlap in a single hire.

#1 The Hybrid Skill Gap

Edge computing demands engineers who are simultaneously embedded firmware developers, cloud architects, and data pipeline specialists. They need to optimize neural networks for a microcontroller with 256KB of RAM in the morning and configure an MQTT broker on AWS IoT Core in the afternoon. This profile barely exists in the labor market.

The Reality:The global deficit of embedded engineering professionals exceeds 1.4 million. Edge computing roles that additionally require cloud and AI/ML skills take 6–9 months to fill – if they can be filled at all.

#2 Embedded Teams Don't Speak Cloud. Cloud Teams Don't Speak Embedded

Most organizations have either a firmware team or a cloud team. Edge computing requires both to work as one – and the translation layer between them is where projects stall. Firmware engineers who have never configured a cloud IoT platform struggle with connectivity architecture. Cloud engineers who have never touched an RTOS cannot optimize for power, memory, or latency constraints.

The Consequence:
Systems that work on the bench but fail in the field. Devices that drain batteries in hours instead of years. Data pipelines that cannot handle intermittent connectivity. Cloud backends that cannot scale beyond the prototype.

#3 Edge AI Is Outpacing Internal Capabilities

The shift from cloud-centric AI to on-device inference (Edge AI, TinyML) is accelerating. But deploying machine learning models on resource-constrained hardware requires a skillset that is part data science, part embedded optimization – a combination that is exceptionally rare. Internal teams that excel at training models in Python often lack the embedded C expertise to deploy them on an MCU.

The Risk:
Companies that cannot execute on edge AI will lose competitive advantage to those that can. The market is not waiting.

Full-stack edge engineers deployed as pre-integrated teams

needCode provides what the edge computing market desperately needs: engineering teams that operate across the entire edge-to-cloud continuum. Our engineers write firmware for resource-constrained MCUs, design cloud integration architectures, build real-time data pipelines, and deploy AI models at the edge — because that is what delivering a complete edge solution requires.

01 Engineers Who Own the Entire Stack

Our teams are not firmware-only or cloud-only. They are full-stack edge engineers who have delivered complete edge-to-cloud systems — from sensor data acquisition on bare-metal MCUs through wireless transmission (BLE, UWB, Wi-Fi, LoRa) to cloud backend processing (AWS IoT, Azure IoT Hub, Google Cloud IoT).

Embedded Edge: Firmware development, RTOS optimization (FreeRTOS, Zephyr), low-power design, sensor fusion, and on-device data processing.
Connectivity Layer: Wireless protocol implementation (BLE, UWB, Zigbee, Matter, Wi-Fi, LoRaWAN) with deep RF stack expertise.
Cloud Integration: Secure MQTT/CoAP connectivity, device management, data pipeline architecture, API development, and backend services.

02 The "Family Unit" Advantage

We do not send individual contractors. We deploy cohesive teams with 5–8 years of shared professional history who have already built edge computing solutions together. This eliminates the months of forming-storming-norming that destroy project velocity.

Retention: In our 5+ year partnership with Qorvo, we scaled to 30 FTEs with only 4 departures.
Continuity: The engineers who design your edge architecture are the same ones who maintain it in production.

03 Connectivity Expertise That Cloud-First Firms Cannot Match

The critical differentiator in edge computing is the connectivity layer — the wireless protocols that move data from sensor to gateway to cloud. This is where most edge computing staff augmentation firms fail. needCode's heritage is wireless connectivity: UWB, BLE, BLE Mesh, Zigbee, Matter, Wi-Fi, LoRaWAN. We do not bolt on connectivity expertise as an afterthought. It is our foundation.

Industries and use cases we serve

Smart Manufacturing & Industry 4.0

Manufacturers deploying predictive maintenance, real-time quality control, and production line optimization need edge computing engineers who understand industrial protocols (CAN, Modbus), sensor data acquisition, on-device anomaly detection, and secure cloud integration for analytics dashboards.

Typical roles needed:
Embedded firmware engineers, Edge AI/TinyML specialists, IoT gateway developers, cloud integration engineers, industrial protocol specialists.

Logistics & Warehousing

Real-time asset tracking, warehouse positioning, fleet monitoring, and autonomous robotics coordination demand edge systems that process location data locally (UWB, BLE), make time-critical decisions without cloud round-trips, and sync with warehouse management systems.

Typical roles needed:
RTLS firmware engineers, UWB/BLE connectivity developers, edge data pipeline architects, WMS integration specialists.

Smart Buildings & Building Automation

BLE Mesh lighting control, occupancy sensing, HVAC optimization, and energy management require edge nodes that aggregate sensor data, run local control logic, and communicate with building management systems — often across thousands of devices with ultra-low power budgets.

Typical roles needed:
BLE Mesh developers, Zigbee/Matter engineers, low-power firmware specialists, cloud-connected building management system integrators.

Healthcare & Wearables

Remote patient monitoring, medical wearables, and clinical trial data collection need edge devices that process vital signs locally (heart rate, SpO2, glucose), detect anomalies in real-time, and transmit securely to healthcare cloud platforms — all while meeting strict power, reliability, and regulatory requirements.

Typical roles needed:
Low-power embedded engineers, BLE connectivity developers, Edge AI for health signal processing, secure cloud integration engineers, regulatory compliance specialists.

Smart Agriculture

Precision agriculture systems — soil monitoring, crop health analysis, automated irrigation, drone-based sensing — require edge devices that operate in remote environments with intermittent connectivity, process sensor data locally, and sync with cloud analytics when bandwidth is available.

Typical roles needed:
Low-power IoT firmware engineers, LoRaWAN/satellite connectivity developers, edge data processing specialists, agricultural automation engineers.

Automotive & EV Infrastructure

Connected vehicles, EV charging infrastructure, and fleet management systems need edge computing for real-time diagnostics, charge session management, V2X communication, and secure OTA updates — all with automotive-grade reliability requirements.

Typical roles needed:
Automotive embedded engineers, CAN bus specialists, secure OTA architects, cloud-connected fleet management developers.

Technical capabilities across the edge computing stack

Edge Device Firmware & Embedded Software

Firmware development in C/C++ for ARM Cortex-M, RISC-V, and application processors.
RTOS expertise: FreeRTOS, Zephyr OS — porting, configuration, task scheduling for multi-protocol workloads.
Board Support Package (BSP) development and hardware abstraction layers.
Power management optimization for battery-operated edge devices.
Sensor integration and sensor fusion (accelerometers, gyroscopes, environmental sensors, radar).
Secure boot, hardware security modules (HSM), and cryptographic implementations.

Wireless Connectivity (Our Core Strength)

UWB: Ranging, RTLS, secure access, radar sensing — Qorvo QM33/QM35, NXP Trimension.
BLE: GATT profiles, BLE Mesh, BLE Audio, Channel Sounding — Nordic nRF52/nRF53, Qorvo QPG6105.
Zigbee & Matter: Multi-protocol coexistence via Qorvo ConcurrentConnect™ — QPG6100, QPG6105, QPG6200L.
Wi-Fi: ESP32, integration with IP networks, power optimization.
LoRa/LoRaWAN: Long-range IoT for remote deployments.
Industrial Protocols: CAN, Modbus for manufacturing and automotive environments.

Edge AI & TinyML

On-device ML model deployment for resource-constrained MCUs.
TinyML inference optimization (model quantization, pruning, knowledge distillation).
Real-time anomaly detection, pattern recognition, and predictive analytics at the edge.
Integration of AI workflows with existing embedded firmware stacks.
Sensor data pre-processing and feature extraction for ML pipelines.

Cloud Integration & Data Pipelines

Secure cloud connectivity via MQTT, CoAP, HTTPS with TLS/DTLS.
Cloud IoT platform integration: AWS IoT Core, Azure IoT Hub, Google Cloud IoT.
IoT device management: secure onboarding, monitoring, OTA firmware updates.
Data pipeline architecture: ingestion, processing, storage, and real-time analytics.
API development and middleware for enterprise system integration (ERP, WMS, BI tools).
Backend services: serverless functions, message queues, time-series databases.

IoT Gateway Development

Gateway firmware and software for multi-protocol aggregation.
Edge processing and data filtering before cloud transmission.
Store-and-forward for intermittent connectivity scenarios.
Local decision-making and control logic.
Secure communication management across device fleets.

Turn Ideas Into Life

Ready to build the future? Partner with needCode to transform complex concepts into reliable, high-performance embedded solutions.

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Edge computing roles available for immediate deployment

Role

Focus Area

Embedded Firmware Engineer

Edge device firmware, RTOS, low-level drivers, power optimization

Wireless Connectivity Engineer

BLE, UWB, Zigbee, Matter, Wi-Fi, LoRaWAN protocol stack development

Edge AI / TinyML Engineer

On-device ML deployment, model optimization for constrained hardware

IoT Gateway Developer

Multi-protocol gateway firmware, edge processing, data aggregation

Cloud Integration Engineer

AWS/Azure/GCP IoT, MQTT/CoAP, device management, data pipelines

Full-Stack IoT Engineer

End-to-end edge-to-cloud development, API and backend services

Software Architect

System/solution architecture, edge-to-cloud design, API versioning

QA Automation Engineer

Automated validation frameworks, protocol-aware testing, CI/CD

Scrum Master

Agile project management for distributed edge computing teams

From first call to integrated edge team in weeks

Step 1

Edge Stack Assessment

We map your project requirements across the edge-to-cloud continuum — firmware, connectivity, cloud, AI — and identify the exact engineering profiles and team composition you need.

Step 2

Pre-Screened Team Proposal

We present candidates from our established talent network. Every engineer has verified experience building edge computing systems with wireless connectivity — not just cloud or just firmware, but the hybrid expertise that edge demands.

Step 3

Fast Integration (< 6 weeks)

Engineers plug into your existing workflows, tools, and codebase. Our Central European location (Kraków, Poland) provides real-time overlap with European teams and morning overlap with US East Coast.

Step 4

Scale Across the Stack

Start with a focused pod — for example, two firmware engineers and a cloud integration specialist — and scale up as your edge deployment grows. Add Edge AI, QA, or architecture capacity as the project evolves.

Flexible models for every stage of your edge computing roadmap

Team Augmentation

Individual engineers or small pods embedded directly into your existing teams. Ideal for plugging specific skill gaps — adding BLE connectivity expertise to a cloud team, or cloud integration skills to a firmware team.

Dedicated Edge Computing Team

A complete needCode team — firmware engineers, connectivity specialists, cloud integrators, QA, Scrum Master — operating as your extended edge computing R&D center. Pre-built team dynamics from Day 1.

Project-Based Delivery

End-to-end ownership of a defined edge computing scope — IoT gateway development, edge-to-cloud data pipeline, edge AI proof of concept — with milestone-based delivery.

Consulting + Execution

Combine our Protocol & Chipset Consulting with engineering execution. We design the edge architecture, select the connectivity stack, then deploy our team to build it.

Case studies

Qorvo: RF Leadership

Context: Rapid scaling for new chipset bring-up.

Scale: Grew from <10 to 30 FTEs.
Output: Supported bring-up of 9 new hardware platforms (SDKs, Drivers, Stacks).
Retention: Zero-churn core team retained for 5+ years.

Dedicated Development Center for RF Solutions

Bluetooth Mesh Smart Lighting Control System

Smart Lighting: Core R&D Extension

Context: Client needed deep, specialized expertise to pivot from proprietary tech to a new global standard.

Service: Deployed a dedicated squad of embedded engineers to function as the client's core R&D team.
Output: Co-authored official Bluetooth SIG protocols and delivered the world’s first certified BLE Mesh stack.
Value: Enabled the client to secure Series A funding and defined the industry standard for smart buildings.

Creative Werks: Innovation rescue

Context: Hardware obsolescence threatened production shutdown.

Action: Full-stack takeover (PCB redesign + Firmware + Mobile App).
ROI: 1230% ($1.6M value generated).
Speed: Payback period of 2–3 months.

NeedCode-case study - IoT Solution for Boat Lift Modernization - cover2s

PowerPollen: AgTech automation

Context: Lack of internal expertise stalled a critical automation project.

Action: Re-architected system using unified MCU and ISOBUS standards.
ROI: 13.8x ($2.9M value generated).
Impact: Enabled $1.9M increase in harvester value.

Strategic Partnership

needCode is an official business partner of Qorvo, bringing over 8 years of proven expertise and trusted service to the technology sector.

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Members of the UWB Alliance

In 2025 we became a member of the UWB Alliance. This strategic step reinforces our commitment to pioneering Ultra-Wideband (UWB) technology.

Nordic Semiconductor

needCode was approved in both – listed as a Design Partner in EMEA, and as a Solution Partner in the Bluetooth Positioning Systems category.

Read about partnership

Proudly Certified for Excellence and Security

needCode is officially certified for:
ISO 9001:2015 – Quality Management
ISO/IEC 27001:2022 – Information Security

ISO certifications reflect our focus on delivering reliable IoT solutions, smart product development, and secure technology services.

Testimonials

“I think the key takeaway from needCode is their ability to adapt and understand the customer's requirements. That took away probably a large portion of what could have been a lot of development time and expense for both companies.”

Bob Folkestad

President at Creative Werks

“One aspect that truly sets needCode apart is its profound expertise in firmware development. Their proficiency in various programming languages, embedded systems and hardware architecture is truly impressive. When faced with difficult problems, their strong problem-solving skills and analytical mindset shine through, allowing them to overcome obstacles with remarkable ease.”

Semeh Sarhan

CEO at Xtrava

“I worked with needCode while leading the NWTN-Berlin team in 2018. A big chunk for our FW development has been outsourced to them and they had proven to iterate very quickly, following specs and deliver on time. It was great working with them. I recommend working with needCode’s team on any Embedded SW development.”

Marco Salvioli Mariani

CTO at NWTN Berlin GmbH

“needCode Team proved to be one of the best engineers I have ever met. The part I like the most about the team is the more difficult an obstacle seems to be, the more motivated they were to find a solution and a way forward.”

Szymon Słupik

CTO at Silvair

“needCode is an outstanding partner. Their quick follow-up, scalability, and extensive professional network set them apart. Their expertise in wireless technologies has been valuable, supporting us from low-level drivers to architecture discussions.”

Tim Allemeersch

Director at Qorvo, Inc.

“needCode did a great job improving the firmware of the Vai Kai connected toys and developing new features, surpassing our expectations multiple times. I would definitely recommend hiring Bartek and needCode for the embedded software projects!”

Matas Petrikas

CEO & Co-founder at Vai Kai UG

Insights

DW1000 is now NRND: how to plan your move to DW3000, QM33 or QM35

Short answer Qorvo now treats the DW1000 as Not Recommended for New Designs (NRND), and the DW1000-based MDEK1001 development kit ships for the last time on 15 December 2026. Products already in the field can keep shipping while parts are available, but new designs should start on the DW3000 family, the QM33 family or the […]

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