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This job has expired (closed 2026-03-20).
Jubilee Insurance Logo

AI ENGINEER II (SYSTEMS DESIGN)

Jubilee Insurance
Nairobi
Full-time
Closes: 2026-03-20

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 operationalizing AI solutions, integrating AI models into production systems, and driving AI initiatives end-to-end with focus on business value delivery. The role combines technical expertise in machine learning, MLOps, and solution engineering with strategic thinking and team collaboration to ensure AI systems are reliable, scalable, and impactful. The ideal candidate has experience deploying AI/ML models, managing ML pipelines, and providing solutions that meet enterprise needs.

Qualifications

1. Bachelor’s degree in Computer Science, AI, ML, Software Engineering, or related technical field
(required).
2. Master’s or PhD in AI, ML, or Computer Science (preferred).
3. Relevant certifications in cloud AI, ML, or MLOps (advantageous).
4. 4–7 years of hands-on AI/ML engineering experience, with at least 2 years in senior or lead roles.
Classified as Non-Business
5. Proven experience operationalizing AI solutions in production environments.
6. Experience implementing MLOps best practices and managing scalable AI workflows.
7. Background in LLM-based solutions, RAG systems, or AI Ops in enterprise contexts.
8. Previous experience mentoring junior engineers and leading cross-functional AI projects.

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