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Strong Tier-1 brand but senior, niche GenAI leadership reduces general applicant density.
High due to specialized GenAI platform, regulatory banking knowledge, and model governance requirements.
Explicit 12+ years, mandated multi-team leadership, regulatory domain and specific tech stack create rigid filters.
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Lead and manage ~15+ agile engineers, including AI-assisted developers, to deliver enterprise-scale Python and GenAI platform solutions aligned with Retail and Wealth Risk objectives.
Define and execute strategy and architecture for AI agent platforms, Python data ecosystems, and full-stack microservices supporting regulatory programs like CCAR and FDIC.
Drive AI Product Development Lifecycle adoption, ensuring compliance with model governance and delivery of scalable, secure, and high-volume data pipelines using modern cloud-native technologies.
12+ years experience in enterprise application development, data engineering, or AI platform engineering with leadership in regulated environments.
8+ years leading multi-team Agile organizations (20+ engineers), including distributed and AI-assisted hybrid teams.
Proficiency in Python, PySpark, Databricks, AI/GenAI platform architecture including LLM integration, AI-assisted development tools (Devin.AI, GitHub Copilot), and microservices/cloud-native deployment (Kubernetes/OpenShift).
Bachelor's degree or equivalent; Master's degree preferred.
Experienced technology leader capable of managing large, hybrid human-AI engineering teams in regulated financial environments.
Strong domain expertise in Retail and Wealth Risk, regulatory reporting (CCAR, FDIC), and data governance for risk analytics platforms.
Proven ability to translate complex regulatory and business requirements into scalable, compliant AI and data engineering solutions, engaging senior business stakeholders effectively.