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

Overview In this role, you will lead the Retail and Wealth Risk Engineering remit within Enterprise Risk Technology, shaping enterprise-scale Python and GenAI platforms. You will define strategy, architecture, and execution for AI-powered data ecosystems and full-stack solutions, guiding a ~15-person product-driven engineering team including AI-assisted developers. You’ll advance AI PDLC, model governance, and regulatory data platforms to support CCAR and FDIC initiatives. You drive cross-functional collaboration with Risk, Finance, and Retail Banking teams to deliver scalable, compliant engineering solutions and set governance standards. Compensation / Benefitscompetitive salarymedical, dental & vision coverage401(k)life, accident, and disability insurancewellness programspaid time off and holidays ResponsibilitiesLead ~15 engineer agile scrum teams, including hybrid human and AI-assisted developersDefine and execute enterprise Python, AI agent platforms, and full-stack data apps strategyServe as senior architect for AI agents, data pipelines, and microservicesDrive AI PDLC adoption with model governance and regulatory complianceDevelop high-volume data pipelines using PySpark, Databricks, Kafka, and Data MeshOversee GenAI agent ecosystems with LLMs and HITL for explainability and auditabilityLead AI-enabled SDLC with Devin.AI, Copilot, and governance guardrailsManage microservices and cloud-native architecture (FastAPI/Spring Boot, Kubernetes/OpenShift, CI/CD)Promote engineering efficiency by reusing enterprise frameworksEnsure data governance, data quality, lineage, and auditability across solutionsPartner with Risk, Finance, and Retail Banking stakeholders to translate requirementsBuild relationships with senior leaders for strategic alignment and cross-functional governanceEstablish engineering standards and governance across teamsMentor senior engineers and managers to foster innovation and accountabilityAssess risk in decision-making and uphold Citi’s reputation and regulatory compliance Key requirements12+ years in enterprise application development, data engineering, or AI platform engineering with leadership in regulated environments8+ years leading multi-team Agile organizations (20+ engineers) including distributed/hybrid AI teamsAdvanced Python, PySpark, Databricks for large-scale data processingExperience architecting enterprise AI/GenAI platforms with LLM integrations and prompt engineeringHands-on with AI-assisted tools like Devin.AI and GitHub CopilotStrong microservices, API, and cloud-native deployment experience (Kubernetes/OpenShift)Experience with event-driven architectures and KafkaDeep understanding of data mesh, data federation, and regulatory data requirementsLeadership, communication, stakeholder management, decision-makingExperience with cloud platforms (AWS, Azure, GCP, Databricks) and modern data ecosystemsFrontend familiarity (React/Angular) for full-stack deliveryClient relationship management with senior stakeholdersPreferred: Retail lending/credit risk and regulatory platforms (CCAR, FDIC), core Retail Banking domains, containerization (Docker) and DevSecOps, AI PDLC and model governance, relevant certificationsleadershipstakeholder managementcommunicationPythonPySparkDatabricks