Vice president lead AI ML engineer

About CITI
Citi's mission is to serve as a trusted partner to our clients by responsibly providing financial 
services that enable growth and economic progress. We have 200 years of experience helping 
our clients meet the world's toughest challenges and embrace its greatest opportunities.
Analytics and Information Management (AIM)
Citi AIM was established in 2003, and is located across multiple cities in India – Bengaluru, 
Chennai, Pune and Mumbai. It is a global community that objectively connects and analyzes 
information, to create actionable intelligence for our business leaders. It identifies fact-based 
opportunities for revenue growth in partnership with the businesses. The function balances 
customer needs, business strategy, and profit objectives using best in class and relevant 
analytic methodologies.
What do we do?
The North America Consumer Bank – Data Science and Modeling team analyzes millions of 
prospects and billions of customer level transactions using big data tools and machine learning, 
AI techniques to unlock opportunities for our clients in meeting their financial needs and create 
economic value for the bank.
The team extracts relevant insights, identifies business opportunities, converts business 
problems into modeling framework, uses big data tools, latest deep learning and machine 
learning algorithms to build predictive models, implements solutions and designs go-to-market 
strategies for a huge variety of business problems.
The Specialized Analytics Sr Anlst (AVP) is a developing role for an AI/ML professional. This 
role is focused on designing and building cutting-edge solutions by harnessing the power of 
both advanced machine learning and Large Language Models. The ideal candidate will have a 
deep understanding of the modern AI landscape, with hands-on experience applying these 
technologies to solve real-world business challenges. You will integrate in-depth specialty area 
knowledge with a solid understanding of industry standards and practices, and will have the 
latitude to solve complex problems independently. This role has a direct impact on the 
business's core activities, and the quality of your work will influence the success of your team 
and its partners. The role will report to the VP leading the team.
Responsibilities:
• Design, develop, and deploy end-to-end solutions leveraging Large Language Models 
(LLMs), with a strong focus on building and optimizing Retrieval-Augmented Generation 
(RAG) systems.
• Apply the fundamentals of Agentic AI to create autonomous and intelligent systems that 
solve complex business problems.
• Utilize a broad range of machine learning techniques, including predictive modeling (e.g., 
Gradient Boosting, XGBoost) and unsupervised learning (e.g., Clustering), to generate 
insights and enhance AI-driven solutions.
• Lead advanced prompt engineering efforts and establish robust testing frameworks to 
ensure the performance, accuracy, and safety of LLM-based applications.
• Work with large and complex datasets to source, clean, and prepare data for both 
traditional modeling and advanced LLM applications.
• Translate complex AI/ML concepts and analytical findings into actionable insights and 
communicate them clearly to both technical and non-technical stakeholders.
• Appropriately assess risk when business decisions are made, demonstrating particular 
consideration for the firm's reputation and safeguarding Citigroup, its clients, and assets, 
by driving compliance with applicable laws, rules, and regulations.
Qualifications:
•10+ years of relevant hands-on experience in an AI, ML, or data science role.
• Strong foundation in classical machine learning algorithms (e.g., Gradient Boosting, 
Clustering, XGBoost) and their practical applications.
• Deep understanding of Large Language Models (LLMs), and proven, hands-on 
experience building end-to-end Retrieval-Augmented Generation (RAG) pipelines.
• Demonstrable expertise in advanced prompt engineering techniques and a strong grasp 
of LLM evaluation and testing methodologies.
• Strong proficiency in Python and its core AI/ML libraries
• Expertise in retrieving and manipulating large datasets using SQL.
• Excellent communication and interpersonal skills, with the ability to build partnerships 
with cross-functional leaders in a matrix work environment.
• A proactive, can-do attitude and a strong willingness to learn and adapt within the rapidly 
evolving AI landscape.
Education:
• Bachelors/University degree or equivalent experience in a quantitative field such as 
Computer Science, Statistics, Engineering, or Mathematics.

•Working Environment: office setting, minimal travel required.
• Effort: minimal physical effort required.

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