Teams at Citi

Leads development of low-latency Java application frameworks and microservices for algorithmic trading platforms. Builds market data replay, backtesting, and simulation utilities; integrates and deploys new products; analyzes complex systems; tunes performance; and contributes to architecture. The role requires expertise in Java, JVM internals, Linux, networking, market data, KDB, and low-latency trading systems. It also involves mentoring developers, engaging stakeholders, managing risk, and documenting system designs.

Build and maintain scalable Snowflake data pipelines, write optimized SQL and stored procedures, automate workflows with tasks and streams, configure data sharing, and develop transformations using Snowpark and Python. Analyze complex datasets, resolve data quality issues, manage code with GitHub, and apply DevOps practices to improve deployment and reliability. The role is hybrid in Dublin and supports data infrastructure for a global financial institution.

Leads global software and AI engineering teams responsible for modernizing legacy enterprise platforms. Drives application development strategy, budget and resource planning, governance, risk management, and delivery outcomes. The role requires expertise in Generative AI, LLMs, prompt engineering, AI guardrails, data privacy, model risk management, Java, and Angular. It also involves mentoring engineering teams, influencing senior stakeholders, managing controls, and integrating AI across the software development lifecycle.