AVP-AI/ML Solution

Job Title:  AVP - AI/ML Solution

Responsibilities

• Act as the primary interface between business leaders and the technical team, translating complex business needs into robust technical requirements and high-impact AI roadmaps
• Lead the communication strategy to explain complex technical AI/ML concepts clearly to non-technical stakeholders across the organization.
• Ensure all deployed models and data pipelines maintain high accuracy, stability, and measurable business impact through rigorous experimentation frameworks
• Oversee and guide the design, development, and production deployment of scalable AI/ML systems
• Define model objectives and success metrics, ensuring all AI/ML initiatives directly drive CX uplift and revenue growth
• Partner deeply with Network, Commercial, and Vendor Management teams to co-create AI-native solutions and champion data-driven decision-making across the organization

Requirements

Technical Skills:

• Bachelor’s or Master’s degree in Computer Science, Information Technology, Statistics or related field.
• Minimum of 7–10+ years of professional experience in Data Science, Machine Learning and  AI Solutions, with at least 2–3 years in a leadership, managerial, or principal consulting role (preferably within the telecommunications or consulting sector)
• Demonstrated success in leading cross-functional teams to design, scale, and deliver complex data pipelines, ingestion architectures, and productionized AI products.
• Deep, hands-on architectural familiarity with Multi-Agent systems and orchestration frameworks
• Expert-level command of Python and deep experience across production frameworks like XGBoost, Scikit-learn, TensorFlow, or PyTorch
• Expert knowledge of Google Cloud Platform (GCP) Data/AI products (Vertex AI, BigQuery, Cloud Run) and big data processing (Spark, Dataproc)
• Strong familiarity with Telco data structures, network performance metrics and open industry frameworks (e.g., TM Forum Open Digital Architecture)
• Robust understanding of production MLOps lifecycles (CI/CD) and enterprise orchestration
• Professional certifications such as Google Certified Professional Machine Learning Engineer or equivalent Cloud Architect/AI credentials are highly regarded

Soft Skills :

• Excellent communication, leadership, and team management skills to effectively direct a technical team and collaborate across a matrixed organization
• Proven ability to lead and drive initiatives independently in a fast-paced, dynamic environment
• Exceptional analytical, conceptual, and strategic problem-solving abilities
• Exceptional ability to articulate complex technical architectures, risks, and AI strategies into clear, actionable business insights for non-technical stakeholders and executive leadership