Responsibilities
- Architect and develop AI-driven applications and data pipelines using Python, ensuring solutions are scalable, maintainable, and aligned with the broader technology strategy.
- Lead the design and implementation of Retrieval-Augmented Generation (RAG) systems and agent orchestration frameworks to deliver intelligent, context-aware solutions.
- Partner with technology and business stakeholders across multiple teams to identify system enhancements and translate requirements into robust technical implementations.
- Define and enforce coding standards, testing practices, and implementation processes to elevate quality and consistency across the engineering team.
- Evaluate complex business and system challenges, applying deep technical expertise to develop innovative and effective solutions.
- Coach and guide mid-level engineers and analysts, providing technical direction and allocating work to support team growth and project delivery.
- Identify and manage technical risks within the development lifecycle, ensuring decisions uphold security, compliance, and platform integrity.
Required Qualifications & Skills
- 6–10 years of experience in software or application development, with a track record of delivering complex technical projects from design through to production.
- Hands‑on proficiency in Python for application development, data ingestion, and ETL processes.
- Practical experience building RAG pipelines and working with agent orchestration frameworks such as ADK, LangGraph, or LangChain.
- Advanced SQL skills with the ability to design and optimize queries across large‑scale datasets.
- Solid understanding of Transformer architecture and its application within production AI systems.
- Demonstrated ability to lead technical teams, manage competing priorities, and deliver results in a fast‑moving environment.
- Clear and effective communicator, able to convey complex technical concepts to both technical and non‑technical audiences.
Beneficial Skills & Qualifications
- Experience with Llama Index for data ingestion and ETL workflows within Python‑based environments.
- Familiarity with graph databases such as Neo4j or equivalent, and experience applying graph‑based approaches to data modelling.
- Exposure to GraphRAG techniques for enhancing retrieval and reasoning within knowledge‑graph‑powered AI systems.
- Knowledge of Model Context Protocol (MCP) and its application in AI agent communication and integration.
- Master’s degree in computer science, Engineering, or a related field.
What We Offer
At Citi, you will work at the intersection of financial services and cutting‑edge AI technology, contributing to projects that operate at genuine global scale. This is an opportunity to take technical ownership, grow your leadership capability, and make a measurable impact within a collaborative, performance‑focused engineering environment.
- Hybrid working arrangement with 3 days in the office and 2 days working remotely, giving you flexibility while staying connected to your team.
- Access to continuous learning and development programs to keep your technical skills current and expand your leadership capabilities.
- The opportunity to work on complex, large‑scale AI systems that directly shape how one of the world's leading financial institutions operates.
- A collaborative engineering culture where senior contributors have genuine influence over technical direction and architectural decisions.
- Competitive financial wellbeing support, including compensation and benefits packages designed for experienced technology professionals.
- Wellbeing support and work‑life balance resources available to all employees globally.
Job Family Group
Technology
Job Family
Applications Development
Time Type
Full time
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 any other characteristic protected by law.
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