**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, GitHub 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** . **Responsibilities** + 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, GitHub Copilot, and MCP platforms through advanced prompt engineering and governance guardrails. + Lead **microservices and cloud-native architecture** using FastAPI/Spring Boot, Kubernetes/OpenShift, 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. **Qualifications** **Required:** + 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 ecosystem** for large-scale data processing and ELT/ETL pipelines. + Proven experience architecting and implementing **enterprise AI/GenAI platforms** , including agentic AI frameworks, LLM integrations, and prompt engineering. + Hands-on experience with **AI-assisted development tools** such as Devin.AI and GitHub Copilot and integrating them into engineering workflows. + Strong experience with **microservices architecture, APIs, and cloud-native deployment (Kubernetes/OpenShift)** . + Strong experience with **event-driven architectures and streaming platforms (Kafka)** . + Deep understanding of **data architecture, data mesh, data federation, and regulatory data requirements** . + Exceptional leadership, communication, stakeholder management, and decision-making capabilities. + Experience with **cloud platforms (AWS, Azure, GCP,



Databricks)** and modern data ecosystems. + Familiarity with **frontend technologies (React/Angular)** for full-stack solution delivery. + Proven **client relationship management experience** , with the ability to engage and influence **senior business stakeholders** , lead strategic discussions, and drive consensus across business and technology teams. **Preferred:** + Strong exposure to Retail lending/Credit **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, Loans, Wealth Lending, Finance and Risk data platforms + Solid **Business Domain Knowledge** with experience working directly with **Retail Banking and Risk organizations** , including understanding of business processes, architecture, and infrastructure. + Experience with **containerization technologies (Docker, Kubernetes)** and DevSecOps practices. + Knowledge of **AI Product Development Lifecycle (AI PDLC)** and **model governance frameworks** . + Relevant industry certifications (e.g., AWS/Azure Data/AI, Kubernetes). **Education** + Bachelor's degree/University degree or equivalent experience. + Master's degree is preferred. ------------------------------------------------------ **Job Family Group:** Technology ------------------------------------------------------ **Job Family:** Applications Development ------------------------------------------------------ **Time Type:** Full time ------------------------------------------------------ **Most Relevant Skills** Please see the requirements listed above. ------------------------------------------------------ **Other Relevant Skills** For complementary skills, please see above and/or contact the recruiter. ------------------------------------------------------ _Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law._ _If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review_ _Accessibility at Citi (https://www.citigroup.com/citi/accessibility/application-accessibility.htm)_ _._ _View Citi's_ _EEO Policy Statement (https://www.citigroup.com/global/eeo-aa-policy)_ _and the_ _Know Your Rights (https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf)_ _poster._ Citi is an equal opportunity and affirmative action employer. Minority/Female/Veteran/Individuals with Disabilities/Sexual Orientation/Gender Identity.

📌 Principal Data GENAI Platform Engineer - Senior Vice President (Chennai)
🏢 Citigroup
📍 Chennai