Lead Agentic AI Engineer - VP (Mississauga)

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

Primary Location Full Time Salary Range $120,800.00 – $170,800.00

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.

#J-18808-Ljbffr