Lead Data Engineer - Vice President

**Role Overview:** As an Applications Development Senior Manager, you will be responsible for managing a team to establish and implement new application systems and programs in coordination with the Technology team. Your main objective will be to drive applications systems analysis and programming activities. **Key Responsibilities:** - Manage one or more Applications Development teams to achieve established goals and handle personnel duties such as performance evaluations, hiring, and disciplinary actions - Utilize comprehensive knowledge and skills across multiple Applications Development areas to provide technical oversight across systems and applications - Review and analyze proposed technical solutions for projects and contribute to formulating strategies for applications development and other functional areas - Develop a deep understanding of how different business areas integrate to achieve business goals - Provide evaluative judgment based on analysis of factual data in complex situations - Impact the Applications Development area through monitoring end results delivery, participating in budget management, and handling day-to-day staff management issues - Ensure essential procedures are followed, contribute to defining standards, and negotiate with external parties when required - Appropriately assess risk in business decisions, demonstrate consideration for the firm's reputation and compliance with laws and regulations, and effectively supervise and create accountability within the team **Qualifications:** - 9-15 years of relevant experience in the Financial Service industry - Experience as an Applications Development Manager and in senior-level Applications Development roles - Stakeholder and people management experience - Demonstrated leadership and project management skills - Basic knowledge of industry practices and standards - Clear and concise written and verbal communication skills **Additional Details:** This job description provides a high-level overview of the work performed. Other job-related duties may be assigned as required. **Role Overview:** As a Vice President (VP) in Data Engineering and Artificial Intelligence (AI), with a focus on Generative AI, you will lead the design, development, and deployment of AI/ML solutions. Your role will involve overseeing data engineering initiatives, driving innovation through Generative AI use cases, and collaborating with cross-functional teams to integrate AI solutions. **Key Responsibilities:** - Lead the design, development, and deployment of AI/ML solutions, focusing on Generative AI technologies - Oversee data engineering initiatives to ensure high-quality data availability for AI/ML models - Identify and implement Generative AI use cases aligning with business objectives, driving innovation - Collaborate with cross-functional teams to integrate AI solutions into existing systems and workflows - Stay updated on advancements in AI/ML, particularly in Generative AI, and drive their adoption - Mentor teams in AI/ML best practices, fostering a culture of innovation and technical excellence - Ensure compliance with data governance, security, and ethical AI standards - Represent the organization in external forums, conferences, and industry events showcasing AI/ML capabilities **Required Skills and Qualifications:** - 12+ years of experience in Data Engineering and AI/ML, with 3+ years of hands-on experience in Generative AI - Strong expertise in AI/ML frameworks such as TensorFlow, PyTorch, and Hugging Face - Proficiency in programming languages like Python and familiarity with Big Data technologies - Deep understanding of data pipelines, data lakes, and data governance principles - Strong problem-solving skills and the ability to translate business challenges into AI/ML solutions - Excellent leadership, communication, and stakeholder management skills - Bachelor's or Master's degree in Computer Science, Data Science, or related field (Ph.D. in AI/ML is a plus) **Preferred Qualifications:** - Experience with cloud platforms (e.g., AWS, Azure, GCP) and their AI/ML services - Knowledge of MLOps practices for model deployment and monitoring - Familiarity with ethical AI principles and frameworks - Publications or patents in the field of AI/ML, particularly Generative AI,