AI Application Engineer

• Conduct research and development on Generative AI 

• Develop AI-driven applications to enhance productivity

• Enhance customer experience through AI solutions

• Apply AI technologies to optimize telecom network operations

• Collaborate with business units to tailor AI solutions

• Stay at the forefront of AI advancements

• Prototype and test AI models for real-world applications

• Ensure scalability and performance of AI models

• Collaborate on AI projects with external partners

• Contribute to AI democratization and internal knowledge sharing

KPIs:

• R&D Output and Innovation: The contribution to AI innovation by the number of prototypes developed, and proof-of-concepts (POCs) completed.

• Successful Deployment of AI Solutions: The number of AI-powered solutions, particularly Generative AI and productivity-enhancing applications, successfully deployed in production environments.

• Collaboration & Knowledge Sharing: Participation in cross-functional teams and contribution to knowledge sharing initiatives, such as internal AI toolkits, training sessions, or the AI democratization program.

• Impact on Customer Experience: The performance and customer satisfaction improvements driven by AI applications.

• Productivity Improvements: The percentage increase in organizational productivity or efficiency resulting from AI-driven automations and process optimizations.

TOP 3-5 DELIVERABLES:

• Development and Deployment of a Generative AI-based Solutions

• AI-powered Productivity Tools for Internal Operations

• Customer Experience Enhancement via AI

• AI-based Telecom Network Optimization Solutions

• AI Innovation and Research Contributions

HIRING REQUIREMENTS:

• Educational Background: Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Electrical Engineering, or a related field.

• Experience: Minimum of 3-5 years of hands-on experience in AI/ML, with a focus on developing models and solutions for productivity, customer experience, and/or telecom networks.

• Technical Expertise: Strong proficiency in AI tools, frameworks, and techniques, with proven experience in applying AI to real-world problems in a business or research context.

• Preferred Background: Experience in the telecommunications industry or related fields where AI is applied to network optimization and customer-facing solutions is a strong advantage.