Senior Lead Python Engineer - Applications Development Group Manager - C14 - RUTHERFORD

Summary

We are seeking a highly motivated and experienced Senior Vice President – Senior Lead, Python Engineering and Generative AI 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 agent platforms, Python-based data ecosystems, 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,

Git Hub Copilot). You will be instrumental in driving the adoption of AI Product Development Lifecycle (AI PDLC), regulatory-compliant data platforms, and scalable GenAI solutions, while aligning technology initiatives with Retail Risk, Wealth Risk, and regulatory programs such as CCAR (14Q/14A) and FDIC.

• Lead multiple agile scrum teams comprising ~15+ 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 Python engineering, AI agent platforms, and full-stack data applications, aligned with Retail and Wealth Risk objectives.
• Serve as the senior architect and technical authority for enterprise-scale AI agents, data engineering pipelines, and microservices-based applications, ensuring scalability, resilience, and security.
• 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 PySpark, Databricks, Kafka, and Data Mesh architecture to support regulatory reporting (CCAR, FDIC) and risk analytics.
• Architect and oversee GenAI agent ecosystems using LLMs (Google ADK, Gemini/Flash), implementing Human-in-the-Loop (HITL) frameworks to ensure explainability, auditability, and compliance.
• Drive AI-augmented software development lifecycle, integrating tools such as Devin.
  
  AI, Git Hub Copilot, and MCP platforms through advanced prompt engineering and governance guardrails.
• Lead microservices and cloud-native architecture using FastAPI/Spring Boot, Kubernetes/Open Shift, and CI/CD pipelines, ensuring high availability 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, and auditability, aligned with enterprise governance processes and regulatory expectations.
• Act as a key partner to Risk, Finance, 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, and cross-functional alignment.
• Establish engineering standards, governance frameworks, and best practices across teams, ensuring consistency, quality, and reuse.
• Mentor senior engineers and engineering managers, fostering a culture of innovation, accountability, 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.

• 12+ years of relevant experience in enterprise application development, data engineering, or AI platform engineering, with a strong track record of leadership in regulated environments.
• 8+ years of experience leading multi-team Agile organizations (20+ engineers), including managing distributed and hybrid AI-assisted teams.
• Advanced expertise in Python, PySpark, and Databricks…