Overview
The AI Acceleration Lead is responsible for accelerating the adoption of AI capabilities across ICT products by participating in product squads to design, prototype, and deliver AI-enabled features. The role contributes hands-on to development and ensures effective integration with the Organization’s AI and Data Platform.
Tasks Summary
- Participate directly in product squads as an embedded AI specialist.
- Contribute hands-on to the development of AI components including backend logic, retrieval and prompt integration, and user interface elements.
- Design and implement functional prototypes and target AI components.
- Develop both backend and User Interface (UI)/User Experience (UX) elements for AI-enabled features.
- Guide product squads in effectively integrating AI features with backend services.
- Design AI-enabled solutions in coordination with Solution Architects.
- Apply AI-specific quality and safety evaluation methods.
- Document patterns, prompts, evaluation methods, retrieval configurations, and UI implementations.
- Provide targeted coaching and structured handover to product squads.
- Develop reusable guidance, prompt libraries, configuration templates, retrieval-integration patterns, and evaluation frameworks.
- Maintain a continuous feedback loop with the AI and Data Platform team.
- Support product teams in preparing user-facing documentation, training material, and adoption guidance.
- Perform any other related tasks as required by the hierarchy.
Experience Requirements
- Minimum of 5 years’ experience in software engineering or AI engineering, including hands-on implementation in production systems.
- Experience of collaborating within Agile product squads and working across multidisciplinary teams.
- Experience participating in or guiding architectural discussions is an asset.
- Experience in international or public-sector organizations is an asset.
Qualification Requirements
- 3-4 years’ University education in Computer Science, Engineering, Artificial Intelligence, or a closely related field.
- Certifications in AI engineering, cloud services, data science, frontend development, or relevant emerging technologies are considered an asset.
