Skip to content
Nairobi · KenyaFree to read
PathrelKE
All careers
Technology

IoT Developer

IoT Developers design and deploy networks of connected devices, enabling smart agriculture, logistics, and energy management across East Africa. By 2026, AI enhances predictive maintenance and data analysis, but human input is critical for hardware integration, edge computing, and security. The role is growing rapidly due to government and private sector investments in digital infrastructure. AI tools streamline code generation, but troubleshooting physical device interactions remains a core human skill.

AI exposure
75 of 100, high exposure
Hiring trend
Growing
Hiring rate
85%
Minimum education
Bachelor

The role

What the work is, what it pays, and what it costs you.

At a glance

Work environment
Office or hybrid/remote, in front of a screen most of the day, with cross functional collaboration across product, design and engineering.
Remote friendly
Yes
Freelance potential
High
Freelance rate
Ksh 200,000
Time to senior
5 years
Adaptation level
High

A day in the role

The day starts with monitoring sensor data from smart agriculture deployments, then debugging firmware issues on IoT devices. The developer collaborates with farmers to interpret data and refine algorithms for predictive maintenance and resource optimization.

What it pays

Kenyan market, per month
Entry
KES 1,500,000
Mid
KES 3,000,000
Senior
KES 5,000,000

The trade offs

In its favour

  • High demand from agriculture and logistics sectors offers competitive salaries, often 80-120K KES monthly for experienced developers.
  • Rapidly growing field with opportunities to work on smart farming, water management, and solar monitoring projects across Kenya.
  • Remote work is common, reducing the impact of Nairobi traffic and allowing flexible schedules.
  • Your work directly improves efficiency in key Kenyan industries like agriculture and energy, creating tangible impact.

Against it

  • Reliable internet and power are inconsistent in many parts of Kenya, leading to project delays and additional costs for backup solutions.
  • Hardware components often have long lead times and import duties, increasing project expenses and complexity.
  • The job market is still niche; many roles require relocation to Nairobi or extended travel to client sites.

In practice

Most IoT developers hold a degree in Computer Science, Electrical Engineering, or Telecommunications from the University of Nairobi, JKUAT, or Dedan Kimathi University. Certifications in CISCO IoT, Arduino, or Raspberry Pi are highly valued. Entry-level roles include junior IoT developer at Safaricom, IBM Kenya, or startups like SunCulture and Twiga Foods. Practical experience through projects (e.g., smart water metres, agricultural sensors) and participation in maker spaces like GearBox or Nairobi Garage are common entry routes. Freelancing on platforms like Upwork also provides initial portfolio building.

Career progression moves from junior developer to senior developer in 3-5 years, then to IoT architect or tech lead. Specialization areas include agricultural IoT, smart cities, and industrial IoT. After 5-7 years, one may lead a team of engineers at a telecom or startup. The 10-year trajectory could reach CTO of an IoT company or head of IoT at Safaricom. Salary growth: 70,000 KES entry-level, 150,000-250,000 KES mid-level, and over 300,000 KES for senior roles.

The IoT market in Kenya is emerging but rapidly growing. Key sectors are agriculture (precision farming, soil sensors), energy (smart grids, solar monitoring), and water (smart metering). Leading employers include Safaricom (M-Pesa IoT platform), Liquid Telecom, IBM Kenya, and startups like Ilara Health. Jobs are concentrated in Nairobi, with growing opportunities in Kisumu (Lake Basin region) and Naivasha (floriculture). Growth is driven by 4G/5G network expansion, government smart city initiatives, and the rise of agritech.

A mid-level IoT developer in Nairobi starts at 8am checking sensor data logs for anomalies. At 9am, they join a standup with the hardware team to discuss firmware issues on an ESP32 deployment. Mid-morning is spent debugging a LoRaWAN connectivity problem for a client in Naivasha. After lunch, they collaborate on PCB design for a new water metre prototype. At 4pm, they test the sensor network in a small field setup at the office. The day ends with documentation and sprint planning for the next two weeks.

Exposure

How much of this a machine can already do, and how that was worked out.

Where this rating sits

1,516 rated careers
75
lowmoderatehigh
020406080100

Rated above 94% of the 1,516 careers in the catalogue, which averages 43. Inside technology the mean is 62, across 125 careers.

What the rating is made of

Share of recorded tasks
Machine does it
38%Software can already complete this work end to end.
Machine assists
51%A person still decides, but the drafting is done for them.
Person does it
11%Judgement, relationships and accountability that do not transfer.

Named task by task

Already automated

  • Writing boilerplate firmware code
  • Predicting device failures from sensor data
  • Optimizing network routing algorithms
  • Generating documentation and test cases

Still human

  • Designing fault-tolerant hardware architectures
  • Troubleshooting physical device failures
  • Interfacing with local installation crews
  • Ensuring regulatory compliance (e.g., data privacy)

Your skills, sorted

40 skills recorded

Worth more with the tools

  • Network Planning and Optimization
  • Enterprise Resource Planning (ERP)
  • Multi-Cloud Architecture Design
  • Cloud Migration Strategy
  • Embedded Systems Hardware Design
  • Data Science
  • Research Methods in Information Science
  • Programming & Coding

Holding their value

  • Wireless Communications
  • Optical Fiber Communications
  • Word Processing
  • Spreadsheet Skills
  • Presentation Skills
  • Email Management
  • Internet Navigation
  • Cloud Security & Compliance

The six things it was scored on

0 to 100 each
Digital surfaceraises exposure
100

How much of the work already happens inside software.

People and inventionlowers exposure
60

Work that needs trust, persuasion or an original idea.

Rule bound thinkingraises exposure
50

Decisions that follow a procedure rather than a judgement.

Regulatory stakeslowers exposure
45

Where a named person has to carry the liability.

Routine intensityraises exposure
40

How much of it repeats in the same shape each time.

Physical presencelowers exposure
5

Work that has to happen in a place, with hands.

Task counts

Tasks recorded
8
Automatable now
1
Still human
3
Displacing
Boilerplate code generation (now AI-assisted),Routine testing and refactoring,Basic data cleaning
Augmenting
AI pair-programming (Copilot),Automated code review and test generation,LLM-accelerated research and analysis
Creating
Applied AI/ML engineering,MLOps and AI reliability,AI product and data-product roles

Sources

Behind the rating
  • Frey & Osborne (2013), 'The Future of Employment', Oxford Martin
  • McKinsey Global Institute, 'The Future of Work' (2017/2023)
  • OpenAI/UPenn, 'GPTs are GPTs' (2023), occupational LLM exposure
  • WEF, 'Future of Jobs Report' (2023)

Getting in

The routes into the role and what each one asks for.

What to study

8 courses

How people get in

  • University Degree

    4 yearsHigh cost

    BSc in Telecommunications or Computer Engineering from UoN, JKUAT, or DeKUT

  • Bootcamp

    6 monthsMedium cost

    Moringa School IoT track or Andela embedded systems program

  • Self-taught

    12 monthsLow cost

    Online courses on Arduino, ESP32, and cloud platforms with portfolio projects

Certifications

  • AWS Certified IoT – Specialty

    Amazon Web ServicesKsh 250,0006 months

  • Cisco Certified Network Associate (CCNA) IoT

    CiscoKsh 180,0009 months

  • Certified IoT Professional (CIoTP)

    IoT CommunityKsh 150,0006 months

  • Google Cloud IoT Certificate

    Google CloudKsh 200,0003 months

Tools of the trade

  • AWS IoT Core

    cloudRequiredPaid

  • ThingSpeak

    analyticsNice to haveFree

  • MQTT

    codeRequiredFree

  • Arduino IDE

    codeRequiredFree

  • Node-RED

    codeNice to haveFree

  • Python

    codeRequiredFree

  • Raspberry Pi OS

    codeRequiredFree

  • C++

    codeRequiredFree

Who hires

Interview preparation

3 questions

  • Explain how you would design a LoRaWAN-based soil moisture monitoring system for a farm in Nakuru, considering power constraints and network coverage.

    TechnicalMid

    Cover sensor selection (e.g., capacitive), LoRaWAN gateways, solar power sizing, data transmission frequency, and integration with cloud dashboards. Address Kenya's 868 MHz regulations.

  • Describe a project where you had to integrate AI for predictive maintenance of IoT devices. What challenges did you face?

    BehavioralEntry

    Highlight specific AI model used (e.g., anomaly detection), data collection from sensors, edge vs cloud processing, and challenges like data quality and device heterogeneity.

  • Imagine your client in Mombasa reports that their smart cargo tracking devices are losing connectivity at the port. How would you diagnose and resolve the issue?

    SituationalMid

    Discuss RF interference from cargo containers, checking LoRaWAN gateway placement, device battery levels, and network server logs. Propose solutions like adding gateways or using cellular backup.

Common misconceptions

  • IoT development requires expensive hardware to start

    Entry-level kits cost under KES 5,000. Many projects run on simulators and affordable microcontrollers.

  • IoT jobs are only available at large corporations

    Startups and agritech firms in Kenya hire IoT freelancers for niche projects like soil sensors and fleet tracking.

What happens next

How the role changes from here, and where it leads.

How the role changes

2024-2030

1 task can already be automated today; expect substantial reshaping by 2030. Success means moving up the value chain — from executing tasks to directing AI and applying judgement.

  1. 2024already here

    AI tools begin displacing routine tasks; practitioners adopt copilots.

  2. 2026already here

    Significant automation of standard sub-tasks; roles consolidate.

  3. 2028projected

    Hybrid human+AI roles dominate; pure-routine work largely automated.

  4. 2030projected

    The iot developer role is reshaped around oversight, judgement and AI-fluency.

The near term

High AI-driven change through 2028 — 34% task automation, with the biggest impact on junior, routine work.

  • ~34% of current routine tasks automated or heavily augmented by 2028
  • Junior/entry work consolidates; the mid-level bar rises
  • Fluency with GitHub Copilot becomes a hiring baseline
  • Pay premium widens for AI-directing practitioners
  • New 'human + AI' hybrid roles emerge in high fields
What to do
For this role, with 1 tasks already automatable, the priority is to stop competing with AI on routine work and start directing it. Master GitHub Copilot and Cursor, deepen Prompt engineering and LLM application development, build a portfolio that shows human + AI fluency. Practitioners who direct AI will out-earn those who don't.

Where pay is heading

2024 to 2030
20242030
Entry100kMid200kSenior400k
flat100k+8%216k+19%476k

Monthly pay in Kenyan shillings, rounded to the nearest thousand. These are projections, not observations.

Growth outlook

Net demand change
30
Over
2024-2030
Drivers
AI adoption across every sector,Kenya's Silicon Savannah and fintech boom
Headwinds
Commoditisation of junior coding

Supply and demand

Demand
85
Supply pressure
3
Balance
High demand

What to learn

  • Prompt engineering
  • LLM application development
  • MLOps
  • AI ethics & safety

Tools worth knowing

  • GitHub Copilot

    Priority: Essential

    AI pair-programming and code completion

  • Cursor

    Priority: Essential

    AI-first code editor for refactoring and feature building

  • Claude / ChatGPT

    Priority: Essential

    Design discussion, debugging, documentation

  • v0 by Vercel

    Priority: Recommended

    Rapid UI generation from prompts

  • Postman AI

    Priority: Recommended

    API testing and generation

Where people move next

5 recorded moves
Systems Analyst65%moderateNonprofit Tech Lead60%moderateResearch And Development Manager40%moderateHealthcare Administrator15%challengingMarketing Strategist5%challenging

Line length under each name is the distance of the move: shorter means more of what you already do carries over. Marked lines are steps up rather than sideways.

  • Healthcare Administrator

    Challenging15% skill overlapPromotion

    IoT developers can transition into healthcare administration by leveraging analytical and system skills, but must learn healthcare operations, regulations, and management.

  • Systems Analyst

    Moderate65% skill overlapLateral

    IoT developers have strong system analysis skills from building integrated solutions, making this a natural lateral move with additional focus on business requirements and process improvement.

  • Research And Development Manager

    Moderate40% skill overlapPromotion

    IoT developers bring deep technical expertise to R&D management, but need to build strategic planning, project management, and leadership skills.

  • Nonprofit Tech Lead

    Moderate60% skill overlapPromotion

    IoT developers are well-suited for nonprofit tech lead roles, applying tech expertise to mission-driven projects, though they must adapt to the nonprofit context and constraints.

  • Marketing Strategist

    Challenging5% skill overlap

    Transitioning from IoT development to marketing strategy requires significant retraining in market research, analytics, and creative strategy, with a potential drop in salary.

Related careers

Kenyan market notes

IoT development is booming in smart agriculture, logistics, and energy management. Nairobi, especially iHub and other innovation hubs, leads demand. AI integration has increased project complexity and rates.

Further reading

Keep this

This role is rated 75 out of 100 today. Save it and the app keeps that number, then tells you by how much it has moved when the record is next reviewed.

Save
Read next