We are seeking a highly motivated and experienced Senior Vice President - Senior Lead, AI, Data & Full Stack Engineering Platforms to lead our Retail and Wealth Risk Engineering organization within Enterprise Risk Technology. This is a senior leadership role responsible for defining strategy, architecture, and execution of enterprise-scale AI platforms, Java/Python engineering ecosystems, data platforms, and full-stack solutions.
The ideal candidate is a forward-thinking technology leader who can effectively manage Product based (PDLC) teams comprising ~15+ engineers, including AI-assisted/virtual developers (e.g., Devin.AI, GitHub Copilot). You will be instrumental in driving the adoption of AI Product Development Lifecycle (AI PDLC), regulatory-compliant data platforms, cloud-native engineering, and scalable GenAI solutions, while aligning technology initiatives with Retail Risk, Wealth Risk, and regulatory programs such as CCAR (14Q/14A/14M) and FDIC
Responsibilities:- Lead multiple Agile Scrum teams comprising ~10+ engineers, including hybrid teams of human engineers and AI-assisted development (Devin.AI, Copilot), ensuring delivery excellence and alignment with business priorities.
- Define and execute the enterprise strategy for Java/Python engineering, AI agent platforms, full-stack applications, and data platforms, aligned with Retail and Wealth Risk objectives.
- Serve as the senior architect and technical authority for enterprise-scale AI agents, full-stack applications, data engineering platforms, and microservices-based solutions, ensuring scalability, resilience, security, and maintainability.
- Drive the adoption and operationalization of AI Product Development Lifecycle (AI PDLC), including model governance, evaluation, deployment, monitoring, and compliance with Model Risk Management (MRM).
- Lead development of high-volume data pipelines and data federation layers using Spark, PySpark, Databricks, Kafka, and Data Mesh architecture to support regulatory reporting (CCAR, FDIC) and risk analytics.
- Architect and oversee GenAI agent ecosystems utilizing enterprise LLM platforms, Agentic AI frameworks, and Human-in-the-Loop (HITL) controls to ensure explainability, auditability, and compliance.
- Drive AI-augmented software development lifecycle, integrating tools such as Devin.AI, GitHub Copilot, and MCP platforms through advanced prompt engineering and governance guardrails.
- Lead microservices and cloud-native architecture using Spring Boot, FastAPI, React, Angular, Kubernetes/OpenShift, and CI/CD pipelines, ensuring high availability, scalability, and performance.
- Drive engineering efficiency and standardization by reusing and repurposing enterprise-level frameworks, platforms, and tools, reducing duplication and accelerating delivery across teams.
- Ensure all engineering solutions incorporate data governance and non-functional requirements, including Data Quality (DQ), data lineage, data tracing, observability, resiliency, and auditability, aligned with enterprise governance processes and regulatory expectations.
- Act as a key partner to Risk, Finance, Data, Compliance, and Retail Banking stakeholders, translating regulatory and business requirements into scalable engineering solutions.
- Build and manage strong relationships with senior business leaders, leading strategic discussions, requirement gathering, roadmap planning, and cross-functional alignment.
- Establish engineering standards, governance frameworks, architecture patterns, and best practices across teams, ensuring consistency, quality, reuse, and operational excellence.
- Mentor engineering managers, architects, and senior engineers, fostering a culture of innovation, accountability, AI adoption, and continuous improvement.
- Appropriately assess risk when business decisions are made, demonstrating particular consideration for the firm's reputation and safeguarding Citigroup, its clients, and assets by ensuring compliance with applicable laws, rules, and regulations, and escalating control issues with transparency.
Preferred:- Strong exposure to Retail Lending, Credit Risk, Wealth Risk, and Regulatory platforms, including CCAR (14Q/14A/14M), FDIC reporting, and enterprise risk aggregation.
- Deep Core Systems expertise in Retail Banking domains such as Cards, Mortgages, Consumer Lending, Wealth Lending, Deposits, Finance, and Risk Data Platforms.
- Strong business domain knowledge with experience working directly with Retail Banking, Wealth Management, Risk, Finance, and Data organizations, including understanding of business processes, architecture, and infrastructure.
- Experience with containerization technologies (Docker, Kubernetes), cloud-native engineering, and DevSecOps practices.
- Knowledge of AI Product Development Lifecycle (AI PDLC), Responsible AI, Model Risk Management (MRM), and model governance frameworks.
- Experience implementing enterprise-scale AI Agents, GenAI solutions, Retrieval Augmented Generation (RAG), Agentic AI frameworks, and Human-in-the-Loop (HITL) controls.
- Experience with Data Mesh, Data Products, Data Federation, Metadata Management, Data Catalogs, and enterprise data governance programs.
- Exposure to cloud platforms (AWS, Azure, Google Cloud Platform, Databricks) and modern enterprise engineering ecosystems.
- Relevant industry certifications such as AWS, Azure, Google Cloud Platform, Kubernetes, Databricks, AI/ML, Architecture, or Cloud Engineering certifications.
Education:- Bachelor's degree/University degree or equivalent experience.
Job Family Group: Technology
Job Family:Applications Development
Time Type:Full time
Primary Location:Rutherford New Jersey United States
Primary Location Full Time Salary Range:$176,720.00 - $265,080.00
In addition to salary, Citi's offerings may also include, for eligible employees, discretionary and formulaic incentive and retention awards. Citi offers competitive employee benefits, including: medical, dental & vision coverage; 401(k); life, accident, and disability insurance; and wellness programs. Citi also offers paid time off packages, including planned time off (vacation), unplanned time off (sick leave), and paid holidays. For additional information regarding Citi employee benefits, please visit citibenefits.com. Available offerings may vary by jurisdiction, job level, and date of hire.
Most Relevant Skills Please see the requirements listed above.
Other Relevant Skills For complementary skills, please see above and/or contact the recruiter.
Anticipated Posting Close Date:Nov 12, 2026
Automated Processing and AIWe use automated processing, including artificial intelligence, for our legitimate business interests (or our reasonable and appropriate business purposes) to identify and align the candidate's skills and abilities with a specific job opening. Additionally, if you so choose, or consent, we can match your skills and abilities to other suitable roles at Citi.
Importantly, all our hiring processes and decisions, including determining your suitability for a role, are conducted, checked, and decided by individuals. Our automated processing and AI do not involve relying on automatic or autonomous decision-making. Please refer to any Jurisdictional Considerations, with specific provisions for your country (where relevant) for further details.
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