Citi
Citi
Citi is a global banking and financial services company serving consumers, corporations, governments, and institutions. Its offerings span consumer banking, credit cards, wealth management, corporate banking, and investment banking, supported by operations in more than 100 countries. As a large international finance organization, Citi brings together teams working across banking, financial services, and fintech.

Python Engineering Lead (Assistant Vice President) – Pune, Hybrid

Lead Python, PySpark, and generative AI engineering for Citi’s banking risk technology platforms. Build scalable data pipelines, microservices, and AI agents for enterprise applications.

Description

  • Design and maintain scalable AI agents that support high-volume ELT and ETL workloads
  • Create and deploy generative AI agents with Google ADK and Google Flash 2.5+ LLMs
  • Enable application automation, data insights, workflow assistance, and human-in-the-loop designs
  • Develop data federation layers for Lambda and Data Mesh architectures using tools such as Starburst
  • Build, deploy, and automate microservice integrations for data-intensive systems
  • Apply cloud-native infrastructure, OpenShift or Kubernetes, and CI/CD pipelines to improve scalability, resilience, and maintainability
  • Connect agentic AI tools and platforms using advanced prompt-engineering techniques
  • Protect data quality, integrity, and security across the full data lifecycle
  • Advance data-engineering practices, standards, and operating processes
  • Manage technology risk, support regulatory compliance, and protect Citi, its clients, and assets

Requirements

  • At least 8 years of experience in large-scale application development, including recent hands-on experience deploying secure, scalable AI agents within applications
  • At least 5 years leading Python and PySpark engineering for enterprise-scale, high-volume ELT and ETL workloads with PySpark and Databricks
  • Hands-on agentic AI development using YAML, JSON, FastAPI or Spring Boot, Google ADK, LLM integrations, Devin.AI or GitHub Copilot, and platforms such as MCP, with advanced prompt-engineering skills
  • Demonstrated experience developing and automating microservice integrations for data-intensive applications
  • Proficiency in Python or Scala
  • Strong SQL skills and experience with relational databases
  • Deep knowledge of data modeling, data warehousing, Data Mesh architecture, and data federation
  • Experience with cloud-based big-data platforms including Cloudera, Databricks, AWS, Azure, or GCP
  • Experience with frontend technologies such as Angular or React JS
  • Practical experience applying AI and machine-learning techniques to business problems
  • Working knowledge of Docker and Kubernetes
  • Experience in data engineering for retail banking products
  • Relevant industry certifications are preferred
  • Bachelor’s degree in Computer Science, Engineering, or a related field
  • A master’s degree is a plus

Benefits

  • Equal opportunity employment
  • Reasonable accommodation is available for persons with disabilities

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