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Senior, specialized AI leadership role in a metro reduces candidate competition.
Requires banking/capital markets domain and AI delivery experience, limiting cross-industry transferability.
Explicit 12+ years, mandatory banking domain experience, and technical stack increase strictness.
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Own end-to-end delivery of AI, data engineering, and cloud transformation programs with full responsibility for planning, execution tracking, governance, quality, and stakeholder reporting.
Lead client engagement by managing expectations, understanding business priorities, driving risk/issue resolution, and providing technical and delivery leadership across AI/ML, GenAI, data platforms, cloud, and enterprise architecture.
Mentor and manage engineering teams to ensure delivery excellence, promote best practices, and collaborate with stakeholders to define solution roadmaps and scalable, secure AI/data solutions.
12+ years of experience in AI engineering, data engineering, cloud technologies, data platforms, or enterprise technology delivery.
Strong experience leading AI engagements and client-facing delivery programs in Banking, Capital Markets, or Financial Services domain with exposure to regulatory, risk, compliance, and data governance environments.
Hands-on knowledge of AI/ML concepts, GenAI solutions, modern data platforms (Databricks, Snowflake, Data Lakes), cloud platforms (AWS, Azure, or GCP), and programming with Python, SQL, Spark, PySpark.
Experience in delivery governance including planning, estimation, risk management, stakeholder reporting, and quality assurance.
Operates effectively at the intersection of technical leadership and client engagement in highly regulated financial services environments.
Proven ability to lead complex AI and data platform delivery programs with accountability for governance and execution discipline.
Experienced in building and mentoring high-performing engineering teams while translating business challenges into practical AI and data-driven solutions aligned with enterprise standards.