AI Engineer, AI Transformation at IDinsight
IDinsight View all jobs
- Nairobi
- Permanent
- Full-time
- Working with IDinsight teams and external clients to understand their current processes and pain points and identifying which of these can be solved with AI-powered tools.
- Working across business functions internally and externally — from research to finance to operations to programmatic challenges — to find ways of creating efficiency gains through AI tools and automation.
- Building and deploying user-facing AI applications: from LLM-based pipelines and agents to workflow automations and internal tools.
- Designing, testing, and iterating on LLM-based solutions — prompt engineering, retrieval-augmented generation, multi-step agent architectures, and API integrations.
- Working across the full stack — frontend, backend, and deployment — to ship tools that people actually use.
- Building dashboards, usage tracking, and analytics to measure the impact of deployed tools.
- Synthesising, visualizing, and communicating results internally with other teams as well as externally with clients: dashboards, plots, interactive viz, presentations and reports.
- Writing blog posts or presenting on lessons learned.
- 2–4 years of professional experience in software engineering, AI/ML engineering, or a closely related technical role.
- Proficiency in Python is required — including web frameworks, API development, and scripting. Please do not apply if you are not comfortable building production-quality Python applications.
- Experience building solutions using Large Language Models. This includes designing prompts, building LLM-based pipelines, retrieval-augmented generation systems, or developing applications that use LLM APIs.
- Ability to work across the full stack: backend (APIs, data pipelines), frontend (basic UI/UX for internal tools), and deployment (containerization, cloud services).
- Working knowledge of SQL and comfort working with structured data.
- Familiarity with version control (Git), CI/CD practices, and writing clean, reproducible code.
- B.S./B.S.E. degree in Computer Science, Software Engineering, Applied Math, Data Science, or a similar technical field.
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