Implementation Engineer - AI/ML Cloud Platform

About the role

CloudFactory is looking for an Implementation Engineer based in Nairobi, Kenya. The role combines technical leadership with customer-facing work: partnering with Solutions Engineers, Product Managers and Delivery teams to co-design scalable solutions, and acting as a trusted technical advisor on the company's platform and the AI/ML data ecosystem.

Key responsibilities

• Lead complex deployments and integrations, considering scalability, security, observability and long-term maintainability.
• Design, manage and optimize infrastructure across AWS, GCP and Azure, focusing on reliability, scalability and cost-efficiency.
• Deploy and maintain data pipelines and orchestration frameworks using tools such as Prefect, with end-to-end monitoring, security compliance and operational readiness.
• Work with customers and solutions engineers to uncover challenges and design tailored solutions, balancing technical feasibility with business value.
• Architect and implement technical workflows, custom integrations and automation, and drive delivery of implementation projects with minimal supervision.
• Mentor junior and mid-level engineers, lead knowledge sharing and propose technical and process improvements.
• Contribute to internal tooling, frameworks and documentation so implementations are scalable and repeatable.

Required profile

• Bachelor's degree in Computer Science, Engineering or a related field with at least 8 years of relevant experience, or a Master's degree with 6+ years, or a PhD with 3+ years in a related field.
• Proven track record of solving complex technical problems and delivering enterprise-scale implementations.
• Demonstrated ability to lead cross-functional initiatives and influence decision-making.
• Experience mentoring peers and driving technical excellence across teams.
• Excellent verbal and written communication skills, able to influence and negotiate with technical and non-technical audiences.

Required skills

• Strong software development background with Python.
• Extensive experience managing cloud infrastructure across AWS, GCP and Azure, including deploying and maintaining AI/ML services and APIs.
• Proficiency with workflow orchestration tools, particularly Prefect.
• Ability to architect and scale secure cloud-native solutions with logging, monitoring and alerting best practices.