Senior AI Data Engineer - Vice President at Citi

Mississauga, Ontario, Canada -

Full Time

Start Date

Immediate

Expiry Date

19 Mar, 26

Salary

0.0

Posted On

19 Dec, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

AI Agents, Data Analytics, Data Science, Large Language Models, Machine Learning, Python, SQL, Software Engineering, Problem-Solving, Communication, Cloud Platforms, Containerization, APIs, Automated Processing, Agent Frameworks, Evaluation Strategies, Technical Documentation

Industry

Financial Services

Description

Agent Design and Development: Design and implement intelligent agents, including their perception, reasoning, planning, and action execution modules. System Architecture: Develop scalable and robust architectures for agentic systems, ensuring high performance, reliability, and security. Machine Learning Integration: Integrate various machine learning models (e.g., LLMs, reinforcement learning, predictive models) to enhance agent capabilities and decision-making. Task Automation: Develop agents that can automate complex tasks, optimize workflows, and solve real-world problems across various domains. Framework and Tooling: Utilize and contribute to agentic AI frameworks and development tools. Evaluation and Optimization: Design and implement metrics and evaluation strategies for agent performance, continuously optimizing and improving agent behavior. Research and Innovation: Stay abreast of the latest advancements in AI, particularly in agent-based systems, autonomous AI, and related fields, and propose innovative solutions. Collaboration: Work closely with cross-functional teams including AI researchers, data scientists, product managers, and software engineers to integrate agentic solutions into broader products and services. Documentation: Create comprehensive technical documentation for agent designs, implementations, and operational procedures. 6+ years of professional experience in software development with a focus on AI, machine learning, or agent-based systems. Experience in finance industry a plus. Programming: Strong proficiency in Python, SQL; Java is a plus. Solid understanding of core AI concepts, including knowledge representation, automated planning, decision-making under uncertainty, and multi-agent systems. Experience with machine learning frameworks (e.g., TensorFlow, PyTorch) and relevant libraries (e.g., Scikit-Learn, NumPy, Pandas). Familiarity with large language models (LLMs) and their application in agentic systems. Familiarity with specific agent frameworks (e.g., LangChain, AutoGen, CrewAI, RAG) or research in multi-agent reinforcement learning. Experience in designing and implementing APIs for AI services. Software Engineering: Experience with software development best practices, including version control (Git), CI/CD pipelines, testing, and code reviews. Problem-Solving: Excellent analytical and problem-solving skills with a creative approach to complex challenges. Communication: Strong written and verbal communication skills, with the ability to articulate complex technical concepts to diverse audiences. Platforms: Experience with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes). Bachelor's degree in computer science, artificial intelligence, robotics, or a related quantitative field, or equivalent experience Master's degree preferred ------------------------------------------------------ AI Agents, Data Analytics, Data Science, Large Language Models (LLMs), Machine Learning (ML), Python Frameworks, Structured Query Language (SQL). ------------------------------------------------------ Automated Processing and AI We use automated processing, including artificial intelligence, for our legitimate business interests (or our reasonable and appropriate business purposes) to identify and align the candidate's skills and abilities with a specific job opening. Importantly, all our hiring processes and decisions, including determining your suitability for a role, are conducted, checked, and decided by individuals. Our automated processing and AI do not involve relying on automatic or autonomous decision-making. Please refer to any Jurisdictional Considerations, with specific provisions for your country (where relevant) for further details. ------------------------------------------------------

Responsibilities

Design and implement intelligent agents, focusing on their perception, reasoning, planning, and action execution. Collaborate with cross-functional teams to integrate agentic solutions into broader products and services.