The Olympus Data Reconciliation and Engineering team is responsible for delivering enterprise solutions and common operating model, which provides scalable, efficient and standardise processing for complex reconciliations in the global processing hubs. We are looking for a candidate who can analyze substantial amounts of raw information to find patterns and build AI/ML models. Critical thinking and problem-solving skills are essential for interpreting data. We also want to see a passion for machine-learning and research.
This role will be responsible for all aspects of Reconciliation platform design and development and the delivery and adoption of our next generation solution.
Key Responsibilities:
As part of the Global Reconciliation Utility (GRU) and Data Engineering team, this role will be responsible for development and implementation of GRU AI ML models strategies.
- GenAI Solution Development: Hands-on implementation, and deployment of scalable, robust agentic AI frameworks and Generative AI solutions for critical banking use cases, ensuring high performance, reliability, and security.
- Full-Stack Application Integration: Build full-stack applications that seamlessly integrate state-of-the-art Machine Learning (ML) and Large Language Model (LLM) tools and services into comprehensive AI solutions.
- AI Advancement & Prototyping: Proactively explore, prototype (Proof of Concept), and integrate the latest advancements in AI, particularly in agent-based systems, autonomous AI, and generative AI technologies.
- Collaboration: Fostering collaboration with cross-functional teams including AI researchers, data scientists, product managers, and software engineers to integrate and scale AI solutions across Citi’s products and services.
- Code Development & Standards: Write high-quality production code, drive proof-of-concepts, and validate architectural decisions through implementation. Set technical standards, guide design choices, and raise the bar for the team.
- Deployment: Take AI-enabled capabilities from early exploration and proof-of-concept through to secure, reliable, and production deployments, focusing on cloud-native, container-first services built to scale for enterprise use.
- Performance Evaluation: Design and implement rigorous metrics and evaluation strategies for AI system and agent performance, driving continuous optimization and behavioral improvement.
Qualifications:
- Experience: 7+ years of deep hands-on experience in engineering and executing scalable enterprise solutions.
- AI Expertise: Deep expertise in AI principles, agent-based systems, machine learning, and advanced software engineering practices.
- Programming Proficiency: Expert proficiency in Python programming language is essential.
- GenAI Frameworks: Proven experience in implementing Generative AI use cases using frameworks like LangChain, LangGraph, ADK.
- LLM Implementation: Advanced knowledge in Large Language Models (LLM), with hands-on experience in implementing LLMs using vector databases and Retrieval-Augmented Generation (RAG), as well as tuning models. Ability to perform solution architecture validations for LLMs.
- ML & NLP: Understanding of machine learning models, experience with Natural Language Processing (NLP) libraries and tools.
- GenAIOps: Experience in putting Generative AI (GenAI) models into production and providing support to them (GenAIOps).
- Containerization: Experience in using Docker to create reproducible and scalable environments.
- Problem-Solving: Strong analytical and problem-solving skills with an aptitude for math and statistics.
- Communication: Excellent communication and collaboration skills, with the ability to engage effectively with diverse stakeholders.
- Self-Motivation: Self-motivated and capable of working independently as well as part of a team in a fast-paced environment.
Education:
• Bachelor’s in Computer Science, Mathematics or equivalent.
• A Master’s degree in preferred
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Job Family Group: Technology------------------------------------------------------
Job Family:Data Science------------------------------------------------------
Time Type:Full time------------------------------------------------------
Most Relevant Skills Please see the requirements listed above.------------------------------------------------------
Other Relevant Skills For complementary skills, please see above and/or contact the recruiter.------------------------------------------------------
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View Citi’s EEO Policy Statement and the Know Your Rights poster.
Skills Required
- 7+ years of hands-on experience engineering and executing scalable enterprise solutions
- Deep expertise in AI principles, agent-based systems, machine learning, and advanced software engineering
- Expert proficiency in Python
- Experience implementing Generative AI use cases using LangChain, LangGraph, or ADK
- Advanced knowledge and hands-on experience implementing LLMs with vector databases, RAG, and model tuning
- Ability to perform solution architecture validations for LLMs
- Understanding of machine learning models and experience with NLP libraries and tools
- Experience deploying and supporting Generative AI models in production, including GenAIOps
- Experience using Docker for reproducible and scalable environments
- Strong analytical and problem-solving skills with aptitude for math and statistics
- Excellent communication and collaboration skills
- Ability to work independently and in a fast-paced team environment
- Bachelor's degree in Computer Science, Mathematics, or equivalent
- Master's degree
Citi Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Citi and has not been reviewed or approved by Citi.
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Healthcare Strength — Health coverage is presented as comprehensive, including free in-network preventive care, mental-health resources, and the Be Well Program. Materials also state new hires have access to health and insurance benefits from the outset.
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Retirement Support — The retirement plan offers a $1-for-$1 match up to 6% of eligible pay. New employees are eligible for the plan, with automatic enrollment after 90 days if they do not enroll themselves.
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Inclusive Benefits Coverage — Benefits highlight fertility treatment coverage, adoption/surrogacy reimbursement up to $30,000, and disability coverage. Coverage extends to spouses and domestic partners regardless of gender identity or sexuality, with gender-affirming care-related support noted.
Citi Insights
What We Do
Citi's mission is to serve as a trusted partner to our clients by responsibly providing financial services that enable growth and economic progress. Our core activities are safeguarding assets, lending money, making payments and accessing the capital markets on behalf of our clients. We have 200 years of experience helping our clients meet the world's toughest challenges and embrace its greatest opportunities. We are Citi, the global bank – an institution connecting millions of people across hundreds of countries and cities.
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