Python Engineering AI Lead-Assistant Vice president

Design, develop, and maintain scalable, enterprise-grade AI agents , supporting ELT/ETL processes to handle large data volumes using the Python, FAST API, Microservices , PySpark, Kafka and Databricks ecosystem.

Build and Deploy GEN AI Agents using Googles ADK and Google Flash 2.5+ LLMs to support application automation supports and its deep insights, workflow support with HIL - Human in loop architecture.

Build and maintain data federation layers for lambda and Data Mesh architectures using tools like Starburst, with a strategy for adopting AI-based use cases (e.g., machine learning, deep learning, NLP) to drive efficiency.

Develop, deploy, and automate microservice integrations to support data-intensive applications, ensuring scalability, resilience, and maintainability using cloud native infrastructure and openshift or Kubernates architecture including CI/CD pipelines.

Integrate and leverage agentic AI tools (e.g., Devin.AI, Github Copilot) and platforms (e.g., MCP) through advanced prompt engineering to enhance development and operational efficiency.

Ensure data quality, integrity, and security throughout the entire data lifecycle.

Contribute to the continuous improvement of data engineering processes, standards, and best practices within the team.

• Appropriately assess risk when business decisions are made, demonstrating consideration for the firm's reputation and safeguarding Citi, its clients, and assets by driving compliance with applicable laws, rules, and regulations. Adhere to Policy, apply sound ethical judgment, and escalate, manage, and report control issues with transparency.