Applicants may express interest in one or both of the following tracks:
1. Software Engineering
Participants may gain practical experience in:
Software development principles and practices
Front-end and back-end application development
Web and mobile application development
Database design and management
Application programming interfaces and system integration
Version control and collaborative development
Software testing and quality assurance
Application security
Cloud deployment and DevOps practices
Technical documentation
Maintenance and improvement of existing software
Enterprise resource planning and business application development
2. Artificial Intelligence and Data
Participants may gain practical experience in:
Data collection, preparation and analysis
Python programming for data and AI applications
Machine learning fundamentals
Generative AI and large language model applications
Prompt engineering and AI-assisted workflows
Retrieval-augmented generation and knowledge systems
Development of chatbots and intelligent assistants
Responsible and ethical use of artificial intelligence
Model testing and performance evaluation
Data visualisation and business intelligence
Integration of AI capabilities into business applications
Automation of business processes using AI
Programme Approach
Structured technical learning
Guided self-study
Mentorship from experienced professionals
Individual and team assignments
Practical laboratory exercises
Participation in supervised client and internal projects
Code reviews and technical demonstrations
Regular performance and learning assessments
Development of a professional project portfolio
Workplace-readiness and professional skills development
Participants will be expected to take responsibility for their learning and progressively demonstrate the ability to apply their knowledge to practical problems.
Who Should Apply?
Be recent graduates or final-year students awaiting graduation
Hold, or be completing, a Bachelor’s qualification in Computer Science, Software Engineering, Information Technology, Information Systems, Data Science, Artificial Intelligence, Mathematics, Statistics, Electrical Engineering or another relevant field
Have a genuine interest in software development, data or artificial intelligence
Possess basic programming knowledge in at least one language
Demonstrate analytical thinking and problem-solving ability
Be willing to learn new technologies independently
Be able to work effectively both individually and as part of a team
Have good written and verbal communication skills
Demonstrate integrity, discipline, curiosity and professionalism
Be available for the full duration of the programme
Note: Knowledge of technologies such as Python, JavaScript, PHP, Java, C#, SQL, Git, cloud platforms, data-analysis tools or AI frameworks will be an advantage but is not mandatory.
What we are looking for
Academic qualifications are important, but selection will also consider:
Ability to learn and apply new concepts
Evidence of personal, academic or community technology projects
Logical and structured problem-solving
Interest in solving real business and social challenges
Creativity and willingness to experiment
Consistency, accountability and attention to detail
Ability to receive and act on feedback
Commitment to completing the programme
Female graduates and applicants from groups that are underrepresented in technology are particularly encouraged to apply.
What Participants will gain
Develop practical, job-relevant technical skills
Work on real software, data and AI use cases
Receive technical mentorship and career guidance
Build a demonstrable portfolio of completed work
Strengthen teamwork, communication and workplace skills
Learn professional software-development processes
Gain exposure to enterprise systems and client environments
Receive a certificate of completion, subject to meeting programme requirements
Be considered for future employment or project opportunities where available
Participant Responsibilities
Attend and actively participate in scheduled sessions
Complete assigned learning activities and practical projects
Meet agreed deadlines and performance standards
Maintain accurate records of their learning and project work
Protect confidential company and client information
Follow Kaone Enterprises’ policies and professional standards
Use company systems, data and equipment responsibly
Participate in progress reviews, demonstrations and assessments
Collaborate respectfully with mentors, colleagues and fellow learners
Programme Terms
The programme will run for 6 months.
Participation will be full-time and delivered onsite.
Selected learners will receive a stipend.
Participation does not automatically create an entitlement to permanent employment.
Continued participation will depend on attendance, conduct, learning progress and satisfactory performance.
Learners may be required to sign confidentiality, intellectual-property, acceptable-use and data-protection agreements.
Any software, documentation, datasets or other work developed during assigned company projects will be handled in accordance with the programme agreement and applicable law.
How to Apply
1Application Requirements
Applicants should submit:
A current curriculum vitae, not exceeding three pages.
A brief motivation letter explaining:
Why they want to join the programme;
Their preferred learning track;
The skills they hope to develop; and
How they intend to apply the experience after the programme.
Copies of relevant academic qualifications or transcripts.
Links to a GitHub profile, portfolio, application, research project or other relevant work, where available.
A copy of a valid national identification document.
2Application Process
Applications should be submitted by email to:
talent@kaone.co.ug
Email Subject Format:
Application – Graduate Software Engineering and AI Learnership – [Applicant’s Full Name]
Application Deadline: 15th August 2026
Only complete applications received before the deadline will be considered. Shortlisted applicants may be required to complete:
A basic technical and problem-solving assessment;
A practical programming or data assignment; and
An interview assessing motivation, learning ability and programme fit.
Only shortlisted applicants will be contacted.
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