Python Engineering AI Lead - Assistant Vice President

Citi; New York (NY); Hybrid; USD 42,000 - 73,000; Full time

Job summary

Citi seeks a Python Engineering AI Lead at AVP level to design and build scalable AI-enabled data pipelines within Retail and Wealth Risk Engineering. You will lead ELT/ETL data workflows, integrate AI agents, and drive data-driven insights across enterprise platforms.

The role emphasizes practical AI deployments, data governance, and collaboration with cross-functional teams to advance Citi's AI capabilities while maintaining risk and regulatory compliance.

Qualifications

• 8+ years of experience in large-scale application development with AI deployment.
• 5+ years leading Python and PySpark engineering for ELT/ETL in Databricks.
• Hands-on AI development with YAML, JSON, FAST API, Google ADK, MCP.
• Experience automating microservice integrations for data-intensive apps.
• Proficient in Python or Scala and strong SQL skills.
• Deep data modeling, warehousing, Data Mesh, and data federation understanding.
• Excellent communication and collaboration skills.
• Experience with cloud big data platforms is preferred.

Responsibilities

• Design, develop, and maintain scalable AI agents supporting ELT/ETL with Python and PySpark.
• Build and deploy GEN AI agents using ADK and LLMs for automation and insights.
• Create data federation layers for lambda and Data Mesh architectures.
• Develop and automate microservice integrations for data-intensive apps.
• Leverage agentic AI tools and platforms via advanced prompt engineering.
• Ensure data quality, integrity, and security across the data lifecycle.
• Contribute to engineering standards and best practices.
• Assess risk and ensure compliance with Citi policies.

Skills

Python

PySpark

SQL

Data modeling

Data warehousing

Docker

Kubernetes

Education

Bachelor’s degree in Computer Science/Engineering

Master’s degree

Tools

Databricks

Google ADK

MCP

FAST API

Kafka

Job description

Python Engineering AI Lead - Assistant Vice President

Location(s):

Pune, Maharashtra, India, Chennai, Tamil Nadu, India

Job Type:

Hybrid

Discover your future at Citi

Working at Citi is far more than just a job. A career with us means joining a team of approximately 219,000 dedicated people from around the globe. At Citi, you’ll have the opportunity to grow your career, give back to your community and make a real impact.

Job Overview

We are seeking a highly motivated and experiencedPrincipal Engineerto join ourRetail and Wealth Risk Engineeringteam under theEnterprise Risk Technologyplatform. This is an intermediate-level position responsible for designing, building, and maintaining robust, scalable data pipelines and solutions that leverage cutting-edge Mandatory platform for the secure and scalable deployment of AI agents, Big Data, Databrick and AI technologies. The ideal candidate is a high-impact individual with a passion for data, analytics, and problem-solving. You will play a key role in driving business engagement and growth by building the next generation of data and analytics platforms.

Responsibilities

• 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 elevate, manage, and report control issues with transparency.

Qualifications

Required:

• 8+ years of overall experience in large-scale application development with recent mandatory platform for the secure and scalable deployment of AI agents into application contexts

• Minimum of 5+ years of proven experience in a Python and pyspark Engineering lead role focused on building enterprise-grade, high-volume ELT/ETL processes using the PySpark and Databricks ecosystem.

• Hands‑on experience with agentic AI development using YAML, JSON, FAST API or Spring boot, Google ADK, LLM itegrations, including Devin.AI or Github Copilot, and integrating models via platforms like MCP using advanced prompt engineering.

• Proven experience developing and automating microservice integrations to support data-intensive applications.

• Proficiency in at least one programming language commonly used for data analytics, engineering, such as Python or Scala.

• Strong SQL skills and experience with various relational databases.

• Deep understanding of data modeling, data warehousing concepts, Data Mesh architecture, and data federation.

• Excellent communication, collaboration, and problem-solving skills.

Preferred:

• Experience with cloud-based Big Data platforms (e.g., Cloudera, Databricks, AWS, Azure, GCP).

• Experience with frontend technologies such as Angular or React JS for building data-driven application interfaces.

• Practical experience applying AI/ML techniques to solve real-world business problems.

• Familiarity with containerization technologies (e.g., Docker, Kubernetes).

• Experience in data engineering within the banking retail products domain (e.g., Cards, Mortgage, Deposits, Wealth Management).

• Relevant industry certifications (e.g., AWS Certified Big Data - Specialty, Azure Data Engineer Associate).

Education

• Bachelor’s degree in Computer Science, Engineering, or a related field.

• Master’s degree is a plus.

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.

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