Python AI Engineer – Retail and Wealth Risk Engineering
We are seeking a highly motivated and experienced Python AI Engineer to join our Retail and Wealth Risk Engineering team under the Enterprise Risk Technology platform. This intermediate‑level position focuses on designing, building, and maintaining robust, scalable data pipelines and AI solutions.
Responsibilities
- Design, develop, and maintain scalable, enterprise‑grade AI agents, supporting ELT/ETL processes to handle large data volumes using Python, FAST API, microservices, PySpark, Kafka, and the Databricks ecosystem.
- Build and deploy GEN AI agents using Google ADK and Google Flash 2.5+ LLMs to support application automation and deep insights with a Human‑in‑Loop architecture.
- Create and maintain data federation layers for lambda and Data Mesh architectures using tools such as Starburst, 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, OpenShift or Kubernetes, and 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 data lifecycle.
- Contribute to continuous improvement of data engineering processes, standards, and best practices within the team.
- Assess risk appropriately when making business decisions, demonstrating consideration for Citi’s reputation and safeguarding the firm, its clients, and assets by driving compliance with applicable laws, rules, and regulations.
Qualifications
Required:
- 5‑8 years of overall experience in large‑scale application development.
- Minimum of 5+ years of proven experience in Python and PySpark engineering 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 integrations, and 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, such as Python or Scala.
- Strong SQL skills and experience with 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 front‑end 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.
Location & Salary
Primary Location: Full Time
Salary Range: $94,300.00 – $141,500.00
Equal Opportunity Employer
Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other characteristic protected by law. If you are a person with a disability and need reasonable accommodation to use our search tools or apply for a career opportunity, please review Accessibility at Citi. View Citi’s EEO Policy Statement and the Know Your Rights poster.
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