Lead Generative AI Engineer Manager, SVP

Citi•Mississauga, ON

7d•Onsite

About The Position

Citi is seeking a highly skilled Lead GenAI Engineer Manager to join the Citi Innovation Labs and spearhead the design and development of cutting-edge AI services. This role is pivotal in driving the creation of enterprise-wide Generative AI platforms that deliver tangible value across all of Citi's lines of business. The ideal candidate will leverage a strong background in high-scale engineering and AI solutions to lead technical teams, define architectural vision, and translate ambiguous business challenges into concrete, scalable implementations. This is a key leadership position focused on building innovative, production-grade AI products that will shape the future of finance.

Requirements

6+ years' experience in the software industry, with proven success in a senior position such as Principal Engineer or Architect.
3+ years' experience serving as a people manager.
Highly experienced in delivering complex technical solutions to production, preferably within the Python and AI/ML ecosystem.
Proficiency in programming languages such as Python.
Passion for and proven hands-on experience integrating with AI/ML technologies.
Experience with cloud architectures and public cloud offerings.
A strong and diverse technical background, with the ability to quickly learn new technologies and influence highly skilled engineering teams.
Excellent communication, leadership, and organizational abilities.
Excellent analytical and problem-solving skills with the ability to think strategically.
Bachelor's degree/University degree or equivalent experience is required.

Nice To Haves

Master's degree is preferred.
Experience in the financial industry is a major advantage.

Responsibilities

Lead the end-to-end development of highly complex AI solutions, infrastructure, and architecture.
Lead and guide a team of engineers and data scientists, reviewing designs and code to uphold the highest levels of engineering standards.
Translate ambiguous product or business problems into clear technical direction, defining success metrics for engineering and data science teams.
Design robust model architectures, retrieval strategies, prompting/orchestration layers, and evaluation frameworks that meet product, reliability, and scalability requirements.
Engage with data-science, technical, and business stakeholders to define and architect solutions for key use-cases across our lines of business.
Actively contribute to software development, both as a hands-on coder and as a reviewer.
Build and maintain core Python-based Generative AI components, including RAG pipelines, model wrappers, orchestration logic, and data loaders using FastAPI, ADK, and internal libraries.
Ensure robust error handling, observability, and test coverage across all codebases.
Manage executive stakeholder relationships in technology, acting as a partner and trusted advisor.
Manage multiple concurrent initiatives and projects of varying sizes and complexity.