Job Description :Our client is looking for a Agentic AI Engineer in Toronto, ON

Must Have Primary Skills :

• We are seeking a highly skilled and experienced Agentic AI Engineer to join our AI Engineering team within the Financial Services division. 
• The successful candidate will be responsible for designing, building, and deploying autonomous and semi-autonomous AI agents that automate complex, multi-step financial workflows, enhance client engagement (e.g., Robo-Advisory), and drive operational efficiency, while adhering to strict regulatory and compliance standards. 
• This is a critical role blending expertise in Large Language Models (LLMs), software engineering, and the regulated environment of banking.

Nice To Have Secondary Skills :

• Design, develop, and implement production-grade AI agents and multi-agent systems using modern orchestration frameworks (e.g., LangChain, LangGraph, CrewAI, or proprietary internal frameworks).
• Architect and optimize Retrieval-Augmented Generation (RAG) pipelines to ground agents in proprietary and secure financial data sources (e.g., CRM, transaction logs, compliance documents).
• Develop robust "Tool Use" capabilities, enabling agents to autonomously interact with banking systems, APIs, and microservices (e.g., for transaction monitoring, loan pre-assessment, or reporting).
• Implement advanced prompt engineering techniques and fine-tuning (where necessary) to guide agent behavior and ensure high-quality, reliable, and compliant outputs.
• Build and maintain the core platform components that facilitate the secure and scalable deployment of AI agents on cloud infrastructure (e.g., Azure, AWS) using containerization (Docker, Kubernetes).
• Embed Responsible AI (RAI) principles, including safety, guardrails, bias detection, and explainability (XAI) directly into agent logic and platform services, ensuring alignment with financial industry regulations.
• Develop comprehensive testing and evaluation harnesses (using frameworks like LangSmith or Langfuse) to measure agent performance (e.g., task success rate, hallucination rate, F1 score) before and after production release.
• Ensure all agents comply with internal risk frameworks, AML (Anti-Money Laundering), KYC (Know Your Customer), and other relevant financial regulatory requirements.
• Partner closely with Data Scientists, Quantitative Analysts, Product Managers, and Compliance teams to identify high-impact use cases (e.g., fraud detection, compliance monitoring, credit scoring).
• Provide technical guidance and evangelize best practices for agentic design and LLM usage across the engineering organization.Stay current with advancements in agentic AI, multi-modal LLMs, and Generative AI research, proposing and prototyping new solutions.

Proven Experience In :
Qualifications Experience:
3+ years of experience in AI/ML engineering, software development, or a related quantitative field, with 1+ years focused specifically on developing and deploying Generative AI or Agentic systems.

Technical Expertise (Must-Have):

• Expert proficiency in Python and developing enterprise-grade, clean, and modular code.
• Hands-on experience with at least one major LLM orchestration framework (e.g., LangChain, LangGraph).Proficiency with cloud platforms (Azure, AWS, or GCP) and related technologies (Docker, Kubernetes).
• Strong understanding of MLOps principles, CI/CD pipelines, and robust system observability (logging, metrics, tracing)

Domain Knowledge:

• Previous experience working within the financial services, wealth management, or other highly regulated industries is strongly preferred.

IND1
Email: [email protected]