Senior Assistant Vice President

Job Summary:

Senior AVP - Generative AI Lead

Key Responsibilities:

• Lead the development and deployment of generative AI models (e.g., GPT, diffusion models, transformers) across various business units.

• Define the AI strategy focusing on generative models to enhance product offerings, customer experience, and operational efficiency.

• Collaborate with business leaders and technology teams to identify high-impact use cases and translate them into AI solutions.

• Oversee research and experimentation to stay ahead of advancements in generative AI and related technologies.

• Manage, mentor, and grow a high-performing team of AI specialists, fostering innovation and technical excellence.

• Ensure ethical AI practices, data privacy, and compliance in all generative AI projects.

• Drive AI infrastructure development and integration with existing technology platforms.

• Present technical insights and strategic recommendations to C-suite executives and stakeholders.

• Build partnerships with external AI vendors, academic institutions, and industry consortia.

Qualifications:

• Master's or PhD in Computer Science, AI, Machine Learning, or related technical field.

• 10+ years of experience in AI/ML, with at least 5 years focused on generative AI technologies.

• Proven track record in leading AI teams and delivering large-scale generative AI projects.

• Deep knowledge of generative AI architectures such as transformers, GANs, VAEs, diffusion models, etc.

• Strong programming skills in Python, TensorFlow, PyTorch, or similar frameworks.

• Experience with cloud AI services (AWS Sagemaker, Azure AI, Google AI) and scalable deployment.

• Strong business acumen and ability to translate AI capabilities into measurable business outcomes.

• Excellent leadership, communication, and stakeholder management skills.

• Understanding of AI ethics, fairness, and regulatory considerations.

Preferred Skills:

• Experience in NLP, computer vision, or multimodal generative models.

• Familiarity with large language models (LLMs) like GPT-4, PaLM, or similar.

• Background in product innovation or AI-driven transformation initiatives.

• Exposure to Agile and DevOps practices for AI/ML workflows.