The Co-operative Bank of Kenya Limited is incorporated in Kenya under the Company Act and is also licensed to do the business of banking under the Banking Act. The Bank was initially registered under the Co-operative Societies Act at the point of founding in 1965. This status was retained up to and until June 27th 2008 when the Banks Special General Meeti...

The Role

Specifically, the successful jobholder will be required to:

• Design, develop, test and maintain AI-enabled application features, services and components for customer-facing and internal solutions, including retrieval-augmented generation, conversational assistants, AI agents, tool-calling workflows, intelligent document processing, recommendations and workflow automation.
• Translate product, process and user requirements into secure, maintainable technical designs and working software aligned to approved architecture and engineering standards.
• Take responsibility for integrating models developed by Data Scientists and approved AI services into production applications. Build and test the application APIs, services, user interfaces and workflow integrations required for secure operation and business adoption, maintaining clear separation between application integration and model development responsibilities.
• Implement and test application-level AI controls appropriate to the approved use case and the Bank’s responsible AI standards. Apply prompt engineering, automated and human evaluation, guardrails, human-in-the-loop controls, fallback behaviour, audit trails, user feedback and explainability features where relevant. Evaluate and document AI output accuracy, safety and consistency, and address identified application-level issues.
• Write clean, reusable and well-tested code; participate in peer reviews; address defects, vulnerabilities, performance issues and technical debt.
• Implement application monitoring for availability, performance, usage, model interaction, cost and business outcomes. Use the resulting metrics to identify and address reliability, latency and cost issues within assigned application components. Coordinate with Integration and Platform Engineers on controlled production releases and issues requiring changes outside those components.
• Coordinate application engineering requirements, dependencies and issue resolution with Product Owners, Data Scientists, Data Engineers, Architects, Integration Engineers, QA, Security and business teams. Deliver the assigned application engineering contributions within cross-functional squads from discovery through adoption.
• Maintain technical documentation, deployment artefacts and support procedures for assigned application components. Investigate and resolve production issues within those components, coordinating with other teams where required. Develop and maintain reusable AI components, libraries and engineering patterns that support consistent delivery across squads.

Skills, Competencies and Experience

The successful candidate will be required to have the following skills and competencies:

• A bachelor’s degree in Computer Science, Software Engineering, Information Technology or a related field.
• Relevant professional certification in software engineering, cloud development, DevSecOps, AI/ML engineering or generative AI is an added advantage.
• At least five (5) years of experience in software or application engineering, including delivery of production systems and integrations, with demonstrated experience building applications that use AI, machine learning or generative AI.
• Demonstrated experience with APIs, modern application frameworks, automated testing and secure software development.
• Hands-on experience building AI-enabled applications using LLM application frameworks and APIs, with the ability to select and apply suitable technologies within the Bank’s approved architecture.
• Demonstrated experience integrating AI/ML or generative AI services into production business applications, including application interfaces and controls for secure and reliable operation.
• Experience in banking, fintech or other regulated digital environments is an added advantage.

• Design, develop, test and maintain AI-enabled application features, services and components for customer-facing and internal solutions, including retrieval-augmented generation, conversational assistants, AI agents, tool-calling workflows, intelligent document processing, recommendations and workflow automation.
• Translate product, process and user requirements into secure, maintainable technical designs and working software aligned to approved architecture and engineering standards.
• Take responsibility for integrating models developed by Data Scientists and approved AI services into production applications. Build and test the application APIs, services, user interfaces and workflow integrations required for secure operation and business adoption, maintaining clear separation between application integration and model development responsibilities.
• Implement and test application-level AI controls appropriate to the approved use case and the Bank’s responsible AI standards. Apply prompt engineering, automated and human evaluation, guardrails, human-in-the-loop controls, fallback behaviour, audit trails, user feedback and explainability features where relevant. Evaluate and document AI output accuracy, safety and consistency, and address identified application-level issues.
• Write clean, reusable and well-tested code; participate in peer reviews; address defects, vulnerabilities, performance issues and technical debt.
• Implement application monitoring for availability, performance, usage, model interaction, cost and business outcomes. Use the resulting metrics to identify and address reliability, latency and cost issues within assigned application components. Coordinate with Integration and Platform Engineers on controlled production releases and issues requiring changes outside those components.
• Coordinate application engineering requirements, dependencies and issue resolution with Product Owners, Data Scientists, Data Engineers, Architects, Integration Engineers, QA, Security and business teams. Deliver the assigned application engineering contributions within cross-functional squads from discovery through adoption.
• Maintain technical documentation, deployment artefacts and support procedures for assigned application components. Investigate and resolve production issues within those components, coordinating with other teams where required. Develop and maintain reusable AI components, libraries and engineering patterns that support consistent delivery across squads.

• APIs
• modern application frameworks
• automated testing
• secure software development
• LLM application frameworks and APIs
• prompt engineering
• automated and human evaluation
• guardrails
• human-in-the-loop controls
• fallback behaviour
• audit trails
• user feedback
• explainability features

• A bachelor’s degree in Computer Science, Software Engineering, Information Technology or a related field.
• Relevant professional certification in software engineering, cloud development, DevSecOps, AI/ML engineering or generative AI is an added advantage.
• At least five (5) years of experience in software or application engineering, including delivery of production systems and integrations, with demonstrated experience building applications that use AI, machine learning or generative AI.
• Demonstrated experience with APIs, modern application frameworks, automated testing and secure software development.
• Hands-on experience building AI-enabled applications using LLM application frameworks and APIs, with the ability to select and apply suitable technologies within the Bank’s approved architecture.
• Demonstrated experience integrating AI/ML or generative AI services into production business applications, including application interfaces and controls for secure and reliable operation.
• Experience in banking, fintech or other regulated digital environments is an added advantage.