Senior Technology Lead, XVA Data Engineering & AI Enablement - SVP

Job d:

Location:

Jersey City, New Jersey, United States Salary: $ - $Category:
Technology, Applications Development, Professional Company:
Citi The Markets Technology XVA group is seeking a visionary, hands-on, and battle-tested Senior Vice President (SVP) – Senior Technology Lead & AI  this critical leadership role, you will define and execute the target-state architectural vision for Citi’s cross-asset X-Value Adjustment (XVA) valuation, risk, and stress testing platforms (encompassing CVA, DVA, FVA, MVA, and KVA). You will spearhead the modernization of mission-critical pricing and risk calculation pipelines using high-performance distributed systems, modern cloud infrastructure (AWS/GCP/Open Shift), microservices, and cutting-edge AI/LLM-enabled software engineering.

As an engineering and technology leader, you will bridge the gap between high-throughput quantitative computing and modern enterprise application architecture. You will pioneer the integration of Agentic AI workflows, Multi-Agent systems, and MLOps, transforming developer productivity across the SDLC and accelerating legacy system modernization into next-generation real-time valuation frameworks.

Key Responsibilities Strategic Architecture & Technical Leadership Target-State Architecture:
Define, champion, and drive the multi-year architecture blueprint for the global XVA platform, ensuring modularity, horizontal scalability, fault tolerance, and ultra-low latency.

Distributed Computing & Persistence:
Architect high-throughput distributed caching, messaging backbones (Apache Kafka), and robust polyglot persistence layers (MongoDB, relational, and vector stores) capable of processing massive intra-day risk simulations.

Technical Judgment & Systems Thinking:
Exercise authoritative technical judgment on framework selection, API contracts, cross-component boundaries, and cloud-native migration patterns (AWS, GCP, Red Hat Open Shift).Core Platform Engineering:
Maintain deep hands-on fluency in Java / Spring Boot and Python, establishing engineering excellence standards, clean design patterns, and robust automated CI/CD pipelines.

AI Enablement, Agentic Workflows & Legacy Modernization Agentic AI & Multi-Agent Frameworks:
Architect and deploy autonomous and semi-autonomous Agentic AI systems to optimize complex pricing workflows, trade lifecycle reconciliations, and stress testing scenario generation.

AI-Assisted SDLC & Developer Productivity:
Drive enterprise-grade AI enablement across engineering pods—integrating LLM-driven coding assistants, automated test generation, semantic code search, and architecture review agents to double engineering velocity.

Legacy Modernization with AI:
Leverage Generative AI and code-reasoning models to reverse-engineer, refactor, and migrate monolithic legacy calculation engines onto modular target-state microservices.

MLOps & Model Governance:
Implement end-to-end MLOps pipelines (Docker, Kubernetes/Open Shift, MLflow) for model tracking, validation, deployment, fairness, interpretability, and strict adherence to internal model governance and ethical AI policies.

Program Execution & Quantitative CollaborationXVA Strategy & Stress Testing Migration:
Lead the delivery of cross-asset XVA technology programs, managing the end-to-end migration of CVA/XVA stress testing engines to the target valuation framework.

Quant & Desk Partnership:
Act as the primary technical partner to Quantitative Analysts (Quants), Financial Engineers, Trading Desks, and Risk Officers, translating mathematical models (SIMM, VaR, Greeks, Monte Carlo simulations) into scalable, production-grade enterprise software.

Agile Program Governance:
Lead cross-functional engineering pods using scaled Agile methodologies; manage technical…