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Lead Agentic AI Engineer – VP (Mississauga)

Citi -
Mississauga, ON

Apply Now

Job details

Full-time
$120,800–$170,800 a year
12 days ago

Qualifications

Spring Boot
TensorFlow
Authentication
Data modeling
Azure
Oracle
Node.js
Law
React
Kubernetes
PyTorch
Spark
Encryption
NoSQL
Git
Google Cloud Platform
MongoDB
Java
Master's degree
SQL
AWS
Docker
Bachelor's
JavaScript
PostgreSQL
Distributed systems
Redis
REST
Angular
Django
Software development
GitHub
APIs
Kafka
Metadata
Keras
Vue.js
Flask
AI
Model evaluation
TypeScript
Python
Spring framework

Full job description

About the Role

Citi's Wholesale Technology organization is seeking an exceptional, hands-on Lead Agentic AI Engineer (VP) to design, build, and deploy cutting-edge agentic AI solutions. This role combines deep technical leadership with architectural ownership — driving adoption of LLMs, agentic workflows, and generative AI platforms to improve efficiency, automation, and risk reduction across Citi's global banking operations. You will operate with an AI-first mindset, emphasizing rapid prototyping, MVP-driven development, and iterative delivery of production-grade AI capabilities.

Key Responsibilities

Agentic AI Design & Engineering

Lead end-to-end design, development, and deployment of large-scale agentic AI solutions using Google Agent Development Kit (ADK) and frameworks such as LangChain, LangGraph
Architect advanced multi-agent systems (perception, reasoning, planning, execution) integrating multiple LLM providers (OpenAI, Anthropic, Google Gemini).
Build AI-powered capabilities using Google Gemini, Vertex AI, Agent Development Kit (ADK), Google A2UI, vector databases, RAG pipelines, semantic search, and advanced prompt and context management.
Engineer autonomous agents incorporating planning, tool usage, memory management, and multi-step reasoning patterns.

Full-Stack AI & Backend Engineering

Develop scalable, high-performance backend services in Python (FastAPI, asyncio) with resilient APIs, event-driven designs, and microservices architectures.
Build and maintain robust data pipelines working with SQL (Oracle, PostgreSQL) and NoSQL (MongoDB) databases.
Implement secure REST APIs and agent interfaces with strong authentication, authorization (OAuth), and encryption best practices.
Optimize AI agent performance, latency, and cost through prompt optimization, caching strategies, and vector index tuning.

Architecture, Strategy & Best Practices

Provide architectural guidance for Next-Generation AI (NGAI) initiatives, ensuring adherence to CTO guidelines and platform standards.
Develop and maintain a strategic roadmap for generative AI adoption, evaluating new models, techniques, and platforms.
Establish and govern best practices for the full AI development lifecycle: prompt engineering, model evaluation, MLOps, and data management.

CI/CD, MLOps & Observability

Drive CI/CD practices integrating automated testing, agent evaluation, code quality gates, containerization, and cloud-native deployment pipelines.
Automate AI model quality, performance testing, and MLOps build processing in the CI/CD pipeline.

Leadership, Mentorship & Collaboration

Mentor AI/ML Engineers on best practices in agentic AI development, Google ADK, and advanced AI technologies.
Champion MVP-driven delivery, rapid iteration, and A/B experimentation to achieve fast time-to-value.
Collaborate with business units to identify high-impact use cases and ensure AI solutions meet business goals.

Required Qualifications & Skills

Experience

6–10 years of relevant experience in an AI/ML development role, Applications Development, or Systems Analysis, with a substantial and demonstrated focus on Python technologies.
Minimum 2+ years of professional experience in software development with a focus on AI, prompt engineering, machine learning, and/or agentic AI systems.
Proven track record as a lead developer for agentic flow design, prompt design, and testing of autonomous AI systems with deep expertise in Google ADK.
Subject Matter Expert (SME) in at least one area of Applications Development, particularly Python application development (Django, Flask, FastAPI).

Programming

Python (expert-level): FastAPI, Django, Flask, asyncio, PySpark — strong fundamentals in algorithms, data structures, concurrency, and design patterns.
Proficient in Java (Spring Boot, Spring Cloud), JavaScript/TypeScript (React, Next.js, Node.js), and SQL/data modeling.
Experience across AWS, Azure, and GCP with Docker, Kubernetes, and CI/CD pipelines. Proficient in MLOps practices including model versioning, deployment, and lifecycle management
Strong foundation in secure API design, microservices, event-driven architecture, and distributed systems with expertise in testing, Git workflows, and performance optimization.

Agentic AI & LLM Frameworks

Deep expertise in LLMs (OpenAI GPT, Gemini, Claude, Llama) with hands-on experience in LangChain, LangGraph, LlamaIndex, AutoGen, CrewAI, and Google ADK.
Familiar with Vertex AI, MCPs, agent communication standards, and AI coding tools including GitHub Copilot, Devin, and Claude Code.
Proven experience building advanced RAG systems (hybrid search, re-ranking, metadata filtering) with vector databases including Pinecone, Weaviate, FAISS, pgvector, and ChromaDB.
Hands-on experience in PyTorch, TensorFlow, Keras, and Scikit-learn including fine-tuning and embeddings.

Good to Have

Performance Optimization: Redis, Hazelcast; low-latency distributed systems.
Data Engineering: ETL/ELT pipelines; Apache Spark, Kafka.
Frontend: React, Angular, Vue.js for full-stack capabilities.

Education:

Bachelor’s degree/University degree or equivalent experience
Master’s degree preferred

This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required.

Job Family Group:

Technology

Job Family:

Applications Development

Time Type:

Full time

Primary Location Full Time Salary Range:

$120,800.00 - $170,800.00

Most Relevant Skills

Please see the requirements listed above.

Other Relevant Skills

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

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. Additionally, if you so choose, or consent, we can match your skills and abilities to other suitable roles at Citi.

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.

This job opening is for an existing job vacancy.

Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law.

If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review Accessibility at Citi.

View Citi’s EEO Policy Statement and the Know Your Rights poster.

Apply Now

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