Head of Artificial Intelligence

Key Responsibilities

Develop and execute Al strategy aligned with business objectives across telecommunications, mobile self-care, healthcare, and web applications.
Lead Al research and innovation to implement advanced machine learning (ML), deep learning (DL), natural language processing (NLP), and generative Al technologies.
Collaborate with product, engineering, and business teams to identify Al-driven opportunities for automation, customer experience, and operational efficiency.
Architect and oversee Al solutions, ensuring scalability, security, and compliance with industry standards.
Lead, mentor, and expand the Al team, fostering a culture of innovation and continuous learning.
Stay ahead of Al trends, tools, and technologies to keep the company competitive in Al-driven applications.
Ensure ethical Al practices and responsible Al deployment across all products.
Develop partnerships with universities, research institutions, and Al communities to drive knowledge sharing and innovation.
Monitor Al performance metrics and optimize models for accuracy, efficiency, and real-world applicability.

Required Qualifications & Experience

Bachelor's/Master's/PhD in Computer Science, Al, Data Science, or a related field.
05+ years of experience in AI/ML development, with at least 2-3 years in a leadership role.
Proven experience in deploying Al-driven solutions in telecommunications, healthcare, or web applications.
Expertise in Al technologies such as machine learning, deep learning, NLP, computer vision, generative Al, and Al-powered automation.
Strong knowledge of Al frameworks (TensorFlow, PyTorch, OpenAl, etc.) and cloud platforms (AWS, Azure, Google Cloud).
Experience with big data processing, MLOps, and Al ethics.
Strong leadership, problem-solving, and decision-making skills.
Ability to communicate Al concepts effectively to technical and non-technical stakeholders
Experience in Al-driven automation in the telecom industry (e.g., predictive maintenance, chatbot solutions, network optimization).
Knowledge of Al applications in healthcare, including medical image processing, predictive analytics, and Al-assisted diagnostics.
Experience in large-scale Al deployments and optimization.