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Tier‑1 bank brand and metro location increase competition despite senior, specialized role.
Regulatory risk, Citibank domain, GenAI/Databricks expertise and leadership needs limit cross-industry portability.
Mandatory 12+ years, multi-team leadership, regulated banking and specialized GenAI/data platform requirements increase strictness.
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Lead and manage ~15+ engineers, including AI-assisted developers, to deliver enterprise AI agent platforms and Python-based data ecosystems aligned with Retail and Wealth Risk objectives.
Define and execute architecture and strategy for AI/GenAI platforms, data pipelines, microservices, and scalable full-stack solutions supporting regulatory programs like CCAR and FDIC.
Drive adoption of AI Product Development Lifecycle, model governance, compliance, and engineering standardization across teams, ensuring high availability, security, and data governance.
12+ years in enterprise application development, data engineering, or AI platform engineering in regulated environments.
8+ years leading multi-team Agile organizations (20+ engineers), including hybrid human and AI-assisted development teams.
Expertise in Python, PySpark, Databricks, AI/GenAI platform architecture, microservices, Kubernetes/OpenShift, Kafka, and cloud platforms (AWS/Azure/GCP).
Bachelor’s degree or equivalent experience; Master’s preferred.
Experienced technology leader with proven ability to align AI and data engineering initiatives with complex regulatory and risk management requirements.
Strong background in implementing enterprise AI agent frameworks, full-stack solutions, and operationalizing AI Product Development Lifecycle in financial services context.
Skilled in stakeholder management and strategic communication across business and technology teams, including Retail banking, Risk, and Finance domains.