Senior AI/ML Engineer (Mississauga)

Job Description Opportunity

This is an opportunity to work at RBC Insurance with a group of technology professionals dedicated to delivering solutions to the insurance business and clients. We are all in with Agile development, DevOps, Open Source, SaaS and contemporary tools and processes. You will have an opportunity to make a real difference by working on some impactful and meaningful projects. Responsibilities

Develop and optimize machine learning models for insurance use cases such as claims automation, customer segmentation, or risk assessment. Build RAG systems and agentic AI systems leveraging specification‑driven development practices, ensuring clear specifications and adherence to agentic governance standards. Implement robust ML pipelines that enable seamless deployment of models into production while ensuring scalability, reliability, and minimal downtime. Collaborate with cross‑functional teams, including data scientists, product managers, software engineers, product owners, designers, quality engineers, and other ML engineers, to integrate AI models into existing insurance workflows and applications. Build automated CI/CD pipelines for the ML model lifecycle, ensuring efficient testing, versioning, and deployment of new features or updates. Continuously evaluate deployed model performance, accuracy, and fairness, monitoring for drift or biases and implementing mitigation measures. Establish agentic governance frameworks and monitoring standards for agentic systems, tracking agent performance and ensuring adherence to specifications and SLAs. Lead context engineering initiatives to optimize prompt design, knowledge retrieval, and model interaction patterns, and implement AI review platforms to validate outputs and ensure compliance with regulatory requirements. Apply harness engineering concepts and frameworks to direct, optimize, and control AI system behavior, establishing safety mechanisms and performance optimization strategies. Maintain comprehensive documentation of models, pipelines, and processes, and participate in SRE setup to support end‑to‑end application in production. Prepare for and provide after‑hour support on an as‑needed basis. Continuously improve software engineering practices, build maintainable products, maintain metrics and monitoring to meet SLAs, and stay up‑to‑date with emerging machine‑learning technologies. Qualifications

Strong programming skills in Python, Java, or C++. 2+ years of hands‑on experience in model development and optimization with advanced ML techniques. Experience with cloud platforms (AWS, GCP, Azure) and MLOps tools. Hands‑on experience with frameworks such as Hugging Face Transformers, LangChain, or OpenAI APIs. Strong understanding of NLP tasks (entity recognition, summarization, text classification). Experience evaluating LLM performance using metrics. Proficiency with creating, maintaining, and troubleshooting DAGs for scheduling and orchestrating ML workflows. Experience integrating Airflow with cloud data storage and ETL pipelines. Experience with data pipelines using Apache Spark or Pandas for structured and unstructured data. Knowledge of AWS SageMaker for building, training, and deploying ML models. Hands‑on experience with AWS services such as S3 and Lambda for managing ML workflows. Strong understanding of software development principles, design patterns, testing, and deployment. Experience with DevOps practices (CI/CD, containerization with Docker and Kubernetes). Understanding of application implementation requirements (risk, privacy, compliance). Excellent communication skills and ability to work effectively with cross‑functional teams. Knowledge of harness engineering concepts to direct and optimize AI system behavior. Preferred: adaptability, critical thinking, growth mindset, management and collaboration skills, verbal and written communication, teamwork, and care for team members. Graduate degree in science, mathematics, statistics or engineering. Experience with Agentic Development Life Cycle (ADLC), specification‑driven development, and agent ecosystem architectures. Experience with agentic governance frameworks, monitoring, and observability for agents, and AI review platforms. Experience in context engineering, prompt optimization, and Retrieval‑Augmented Generation (RAG) systems. Experience with agent frameworks, LLM orchestration platforms, or agent evaluation tools. Knowledge of agentic AI governance and responsible AI practices. Benefits

Competitive compensation, commissions, stock where applicable, and a comprehensive Total Rewards Program. Bonuses, flexible benefits, and leadership support for development through coaching. Opportunity to make a lasting impact and work in a dynamic, collaborative, high‑performing team. World‑class training program in financial services and flexible work/life balance options. Opportunities to take on progressively greater accountability and build close relationships with clients. Access to a variety of job opportunities across business and geographies. Additional Job Details

Address: Meadowvale Business Park, 6880 Financial Dr, Mississauga, Canada. Work hours: 37.5 per week. Employment type: Full time (Regular, Salaried). Equal Opportunity Statement

We believe an inclusive workplace that has diverse perspectives is core to our continued growth as one of the largest and most successful banks in the world. Maintaining a workplace where our employees feel supported to perform at their best, effectively collaborate, drive innovation, and grow professionally helps bring our Purpose to life and create value for our clients and communities. RBC strives to deliver this through policies and programs intended to foster a workplace based on respect, belonging and opportunity for all.

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