AI Applied Senior Engineering Lead

Citigroup

Mississauga

On-site

CAD 205,000 - 308,000

Full time

2 days ago

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Job summary

Citi in Mississauga invites an experienced AI Applied Senior Engineering Lead to design, build, and deploy cutting‑edge AI capabilities for Investment, Corporate, and Commercial Banking. You will create scalable, agentic AI frameworks and generative solutions in small, agile squads.

You will work hands‑on with LLMs, multi‑provider platforms, and full‑stack AI apps, emphasizing MVP‑driven delivery, robust security, and production readiness while mentoring junior engineers.

Qualifications

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.

Responsibilities

AI Solution Development: Design, implement, and deploy scalable agentic AI frameworks and generative AI solutions for critical business use cases, ensuring robustness, performance, security, and reliability.
Agentic Systems: Develop and integrate agentic AI systems leveraging multiple model providers and platforms (OpenAI, Anthropic, Google APIs).
Full‑Stack AI Engineering: Build full‑stack applications integrating LLM‑driven workflows and AI coding tools (Devin, GitHub Copilot).
Iterative Delivery: Drive an MVP‑first, rapid‑iteration approach with continuous experimentation and improvement.
Evaluation & Optimization: Define and implement metrics, evaluation strategies, and feedback loops to continuously improve AI system performance and behavior.
Emerging Technologies: Research, prototype, and integrate advances in agent‑based, autonomous, and generative AI technologies.
Technical Collaboration: Contribute hands‑on within cross‑functional teams and mentor junior engineers.
Domain Alignment: Ensure AI solutions align with banking and financial services requirements and constraints.

Skills

Python

Java

JavaScript/TypeScript

LLMs

RAG

Prompt engineering

MCPs

Agent frameworks

Git

CI/CD

Agile

Data analysis

Education

Bachelor's or Master's degree in CS/AI/Robotics

Tools

TensorFlow

PyTorch

Scikit-learn

NumPy

Pandas

Devin

Claude Code

GitHub Copilot

Antigravity

Docker

Kubernetes

OpenShift

Spring Boot

Angular

Node.js

Job description

Role Overview

Citi's Banking Technology organization is seeking a highly hands‑on AI Applied Senior Engineering Lead to design, build, and deploy cutting‑edge AI solutions for 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.

Key Responsibilities

AI Solution Development: Design, implement, and deploy scalable agentic AI frameworks and generative AI solutions for critical business use cases, ensuring robustness, performance, security, and reliability.
Agentic Systems: Develop and integrate agentic AI systems leveraging multiple model providers and platforms (e.g., OpenAI, Anthropic, Google APIs).
Full‑Stack AI Engineering: Build full‑stack applications integrating LLM‑driven workflows and AI coding tools (e.g., Devin, GitHub Copilot).
Iterative Delivery: Drive an MVP‑first, rapid‑iteration approach with continuous experimentation and improvement.
Evaluation & Optimization: Define and implement metrics, evaluation strategies, and feedback loops to continuously improve AI system performance and behavior.
Emerging Technologies: Research, prototype, and integrate advances in agent‑based, autonomous, and generative AI technologies.
Technical Collaboration: Contribute hands‑on within cross‑functional teams and provide technical guidance and mentorship to junior engineers.
Domain Alignment: Ensure AI solutions are well‑aligned to banking and financial services requirements, constraints, and business outcomes.

Qualifications

Programming: Strong proficiency in Python and/or Java (Spring Boot); working knowledge of JavaScript/TypeScript (Angular, Node.js). Full‑stack experience is a plus.
AI/ML Expertise: 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, Claude Code, GitHub Copilot, and Antigravity.
Software Engineering: Strong grounding in modern engineering practices including Git, CI/CD, testing, code reviews, agile delivery, application resiliency, and security.
Architecture: Experience designing API‑first, microservices‑based and event‑driven architectures, including data engineering patterns for AI systems.
Platforms: Hands‑on experience with Docker, Kubernetes, and OpenShift.
Problem Solving & Communication: Strong analytical skills with the ability to clearly communicate complex technical concepts.
Domain Knowledge: Solid understanding of banking/financial services and regulated environments.
Nice to Have: Experience in data science (statistical modeling, experimentation) and interest in mentoring junior AI engineers.

Experience

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.

Education