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This job has expired (closed 2026-02-04).
Jubilee Insurance Logo

AI ENGINEER -FULLSTACK

Jubilee Insurance
Nairobi
Full-time
Deadline: 2026-02-04

About Jubilee Insurance

was established in August 1937, as the first locally incorporated Insurance Company based in Mombasa. Jubilee Insurance has spread its sphere of influence throughout the region to become the largest Composite insurer in East Africa, handling Life, Pensions, Asset Management and Medical Insurance. Today, Jubilee is the number one insurer in East Africa with over 1.9 million clients. Jubilee Insurance has a network of offices in Kenya, Uganda, Tanzania, Burundi. It is the only ISO certified insurance group listed on the three East Africa stock exchanges – The Nairobi Securities Exchange (NSE), Dar es Salaam Stock Exchange and Uganda Securities Exchange. Its regional offices are highly rated on leadership, quality and risk management and have been awarded an AA- in Kenya and Uganda, and an A+ in Tanzania. For more information, visit www.JubileeInsurance.com

Description

The Role holder is responsible for designing, developing, and deploying end-to-end AI-powered features across both backend systems and user-facing applications, ensuring seamless integration of intelligent capabilities into Jubilee’s digital platforms. The role combines strong machine learning expertise with fullstack engineering skills to deliver scalable, high-performing AI solutions that enhance customer experience, automate workflows, and support data-driven decision-making within a fast-paced, product-driven environment.

Qualifications

1. Bachelor’s degree in Computer Science, Software Engineering, Mathematics, or a related field.
2. Relevant certifications in AI, cloud platforms, or software engineering are an added advantage.
3. Demonstrated portfolio of fullstack or AI-driven projects (e.g., GitHub, deployed applications) is
beneficial.
4. 2–3 years of experience in AI engineering, software engineering, or fullstack development.
5. Proven experience building and deploying end-to-end applications with AI components.
6. Experience integrating AI/ML models into production systems and user-facing platforms.
7. Experience working in agile, product-driven environments.
8. Exposure to LLM-based applications and modern AI tools is advantageous.

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