Citi, the leading global bank, has approximately 200 million customer accounts and does business in more than 160 countries and jurisdictions. Citi provides consumers, corporations, governments, and institutions with a broad range of financial products and services, including consumer banking and credit, corporate and investment banking, securities brokerage, transaction services, and wealth management.
As a bank with a brain and a soul, Citi creates economic value that is systemically responsible and in our clients’ best interests. As a financial institution that touches every region of the world and every sector that shapes your daily life, our Enterprise Operations & Technology teams are charged with a mission that rivals any large tech company. Our technology solutions are the foundations of everything we do from keeping the bank safe, managing global resources, and providing the technical tools our workers need to be successful to designing our digital architecture and ensuring our platforms provide a first-class customer experience. We reimagine client and partner experiences to deliver excellence through secure, reliable, and efficient services.
Our commitment to diversity includes a workforce that represents the clients we serve from all walks of life, backgrounds, and origins. We foster an environment where the best people want to work. We value and demand respect for others, promote individuals based on merit, and ensure opportunities for personal development are widely available to all. Ideal candidates are innovators with well-rounded backgrounds who bring their authentic selves to work and complement our culture of delivering results with pride. If you are a problem solver who seeks passion in your work, come join us. We’ll enable growth and progress together.
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 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.
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- 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 Kubernetes 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.
Required:
- 5-8 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 integrations, 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.
Please see the requirements listed above. ------------------------------------------------------
Other Relevant Skills
For complementary skills, please see above and/or contact the recruiter. ------------------------------------------------------
Automated Processing and AI
We use automated processing, including artificial intelligence, for our legitimate business interests (or our reasonable and appropriate business purposes) to identify and align the candidate's skills and abilities with a specific job opening. Additionally, if you so choose, or consent, we can match your skills and abilities to other suitable roles at Citi.
Importantly, all our hiring processes and decisions, including determining your suitability for a role, are conducted, checked, and decided by individuals. Our automated processing and AI do not involve relying on automatic or autonomous decision-making. Please refer to any Jurisdictional Considerations, with specific provisions for your country (where relevant) for further details.
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 a
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