Senior AI Engineer, Banking Technology – Vice President

Citi•Mississauga, ON

2d•CA$120,800 - CA$170,800•Onsite

About The Position

Citi’s Banking Technology organization is seeking a highly hands-on Senior AI Engineer to design, build, and deploy cutting‑edge AI solutions across Investment, Corporate, and Commercial Banking. This role focuses on implementing scalable, agentic AI frameworks and generative AI solutions within small, agile squads. The successful candidate will operate with an AI‑first mindset, emphasizing rapid prototyping, MVP‑driven development, and iterative delivery of production‑grade AI capabilities.

Requirements

6–10 years of progressive software engineering experience with a strong hands‑on coding background.
2+ years focused on AI software development, LLM‑based solutions, agentic systems, and/or machine learning.
Demonstrated experience delivering enterprise‑scale AI capabilities into production.
Strong proficiency in Python and/or Java (Spring Boot); working knowledge of JavaScript/TypeScript (Angular, Node.js).
Full‑stack experience is a plus.
Solid understanding of core AI concepts such as knowledge representation, planning, and multi‑agent systems.
Hands‑on experience with LLMs, RAG, prompt engineering, MCPs, and agent frameworks (e.g., Google ADK).
Practical experience with ML frameworks and libraries (TensorFlow, PyTorch, Scikit‑learn, NumPy, Pandas).
Familiarity with AI coding tools such as Devin, GitHub Copilot, and Antigravity.
Strong grounding in modern engineering practices including Git, CI/CD, testing, code reviews, agile delivery, application resiliency, and security.
Experience designing API‑first, microservices‑based and event‑driven architectures, including data engineering patterns for AI systems.
Hands‑on experience with Docker, Kubernetes, and OpenShift.
Strong analytical skills with the ability to clearly communicate complex technical concepts.
Solid understanding of banking/financial services and regulated environments.

Nice To Haves

Experience in data science (statistical modeling, experimentation) and interest in mentoring junior AI engineers.

Responsibilities

Partner with multiple management teams to ensure appropriate integration of functions to meet goals as well as identify and define necessary system enhancements to deploy new products and process improvements
Resolve variety of high impact problems/projects through in-depth evaluation of complex business processes, system processes, and industry standards
Provide expertise in area and advanced knowledge of applications programming and ensure application design adheres to the overall architecture blueprint
Utilize advanced knowledge of system flow and develop standards for coding, testing, debugging, and implementation
Develop comprehensive knowledge of how areas of business, such as architecture and infrastructure, integrate to accomplish business goals
Provide in-depth analysis with interpretive thinking to define issues and develop innovative solutions
Serve as advisor or coach to mid-level developers and analysts, allocating work as necessary
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, adhering to Policy, applying sound ethical judgment regarding personal behavior, conduct and business practices, and escalating, managing and reporting control issues with transparency.
Design, implement, and deploy scalable agentic AI frameworks and generative AI solutions for critical business use cases, ensuring robustness, performance, security, and reliability.
Develop and integrate agentic AI systems leveraging multiple model providers and platforms (e.g., OpenAI, Anthropic, Google APIs).
Build full‑stack applications integrating LLM‑driven workflows and AI coding tools (e.g., Devin, GitHub Copilot, Antigravity).
Drive an MVP‑first, rapid‑iteration approach with continuous experimentation and improvement.
Define and implement metrics, evaluation strategies, and feedback loops to continuously improve AI system performance and behavior.
Research, prototype, and integrate advances in agent‑based, autonomous, and generative AI technologies.
Contribute hands‑on within cross‑functional teams and provide technical guidance and mentorship to junior engineers.
Ensure AI solutions are well‑aligned to banking and financial services requirements, constraints, and business outcomes