Nathan Tettey Luornor
@nathantetteyluornor
Computer engineer focused on frontend engineering and backend APIs.
What I'm looking for
I am a computer engineering graduate with hands-on experience building responsive web and mobile interfaces using Next.js and developing backend APIs with Django. I have collaborated across multidisciplinary teams, applied test-driven development, and delivered scalable components that reduced UI bugs and improved performance.
I have served as a teaching assistant for Data Structures and Algorithms, mentored students on course projects, and led backend development for healthcare and banking systems. I bring a strong foundation in data structures, algorithms, and full-stack development, and I seek opportunities to apply these skills to deliver reliable, user-focused software.
Experience
Work history, roles, and key accomplishments
Teaching Assistant
University of Ghana
Oct 2024 - Aug 2025 (10 months)
Assisted teaching Data Structures and Algorithms to undergraduate Computer Engineering students and mentored course projects to improve technical implementation and problem-solving.
Software Engineer (Frontend)
Africato Silicon Valley
May 2023 - Dec 2024 (1 year 7 months)
Built responsive, high-performance web and mobile interfaces with Next.js, collaborating with 25+ team members to implement modular components and TDD, reducing UI bugs by 20% and improving scalability.
Software Engineering Intern
Mesika Limited
Apr 2023 - May 2023 (1 month)
Developed backend APIs for a bank management system using Django, designing endpoints to ensure efficient data retrieval and manipulation.
Education
Degrees, certifications, and relevant coursework
University of Ghana
Computer Engineering
2021 - 2024
Grade: 3.72/4.00
Activities and societies: Honors: Mr. Frederick Attakumah Prize and GHIPSS Award for best graduating project; Relevant coursework: Object-Oriented Programming, Data Structures, Web Design and Programming, Introduction to Data Science, Database Systems, Operating Systems; Member of Google Machine Learning Programme.
Completed a Computer Engineering program with a 3.72/4.00 GPA and received awards for the best graduating project in Computer Engineering.
Availability
Location
Authorized to work in
Job categories
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