Senior AI and Machine Learning Engineer - Assistant Vice President

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

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Job Family:

Data Science

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Time Type:

Full time

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Most Relevant Skills

Please see the requirements listed above.

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Other Relevant Skills

For complementary skills, please see above and/or contact the recruiter.

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