What is the opportunity?
This is an opportunity to work at RBC Insurance with a group of technology professionals dedicated to deliver solutions to Insurance business and clients. We are all in with Agile development, DevOps, Open Source, Software as a Service (SaaS) and modern tools and processes. You will have an opportunity to make a real difference by working on some impactful and meaningful projects.
We are looking for an enthusiastic and skilled Senior Machine Learning and AI Engineer to join our AI initiatives Squad, work on the development and deployment of cutting-edge machine learning models, drive innovation, and collaborate with cross-functional teams to drive business growth and improvement. The candidate will have a strong background in machine learning models and algorithms, software development and leadership, with a proven track record of delivering high-quality solutions that meet business needs. The person will collaborate closely with team members under Agile Squad including product owners, Data Scientists, Designers, Quality Engineers and other ML Engineers.
Additionally, the candidate demonstrates expertise in Agentic Development Life Cycle (ADLC), specification-driven development, knowledge of agent ecosystem, agentic governance and monitoring, context engineering, AI review platform, and is well versed with harness engineering concepts to direct AI.
The candidate posts deep understanding of data management principles, modern data stack, cloud computing and ability to apply them in practical, business-focused context. Partners across IT and with assigned business line(s) to assess, research, and analyze business, technical and system needs in order to resolve business systems issues. Recommends technology solutions that meet sponsor / stakeholder needs. Acts as primary IT liaison with multiple interfacing applications, third party vendors, IT Executives, and/or Project Managers.
Our applications are used by RBC staff and clients making your contributions highly impactful and visible, directly contributing to the success of RBC. We deliver digitally enabled applications that are both internal and internet facing. We build Cloud Data Lakehouse, stable web, and back-end applications which are resilient, scalable and high performance that avoids failure and focused on delivering best client experience. We continuously update our tech skills and upgrade our platforms to match industry standards.
What will you do?
Develop and Optimize Machine Learning Models: Refine predictive models tailored 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 they are built with clear specifications and adherence to agentic governance standards.
Ensure Scalable Model Deployment: Implement robust ML pipelines that enable the seamless deployment of models into production while ensuring scalability, reliability, and minimal downtime.
Collaborate with Cross-functional Teams: Work closely with data scientists, product managers and software engineers to integrate AI models into existing insurance workflows and applications.
Streamline Pipeline Releases: Build automated CI/CD pipelines for ML model lifecycle management, ensuring efficient testing, versioning, and deployment of new features or updates.
Maintain and Monitor Model Performance: Continuously evaluate deployed models' performance, accuracy, and fairness. Implement monitoring systems to detect and mitigate model drift or biases. Establish agentic governance frameworks and monitoring standards for agentic systems, tracking agent performance and ensuring adherence to defined specifications and SLAs.
Context Engineering & AI Review: Lead context engineering initiatives to optimize prompt design, knowledge retrieval, and model interaction patterns. Implement AI review platforms to validate model and agent outputs, ensure compliance with regulatory requirements, and maintain solution quality standards.
Harness Engineering for AI: Apply harness engineering concepts and frameworks to direct, optimize, and control AI system behavior, establishing safety mechanisms and performance optimization strategies.
Document and Share Knowledge: Maintain comprehensive documentation of models, pipelines, and processes.
Maintain and Monitor Production Applications: Participate in SRE setup to support end-to-end application in production. Ready to provide after hour support on need basis.
Enhance Operational Efficiency: Keep software engineering practice in mind, build products that can be maintain with least incidents, maintain metrics and monitoring to meet Service and Operational Level Agreements.
Emerging Technology: Stay up-to-date with the latest advancements in machine learning and related emerging technologies, share knowledges with teams and apply the knowledge to improve existing systems and develop new ones.
What do you need to succeed?
Must Have
Strong programming skills in languages such as Python, java, or C++. Experience with cloud platforms (AWS, GCP, and Azure) and MLOps tools.
2+ years of hands-on experience in model development and optimization, with knowledge of advance ML techniques. Hands-on experience with frameworks like Hugging Face Transformers, LangChain, or OpenAI APIs.
Strong understand of NLP tasks such as entity recognition, summarization, text classification.
Skills in evaluating LLM performance using metrics.
Proficiency in creating, maintaining, and troubleshooting DAGs for scheduling and orchestrating ML workflows. Experience in integrating Airflow with cloud data storage and ETL pipelines.
Past experience in data and AI/ML space would be preferred.
Experience with data pipelines using tools like Apache Spark or Pandas for handling structured and unstructured data.
Understand the tools like AWS SageMaker for building, training, and deploying ML models. Hands-on experience with AWS cloud services, such as S3, Lambda, for managing ML workflows.
Strong understanding of software development principles, including design patterns, testing, and deployment. Experience with DevOps practices such as CI/CD, experience with containerization using Docker and Kubernetes.
Strong understanding of application implementation requirements, including risk, privacy, and compliance.
Excellent communication skills with the ability to work effectively with cross-functional teams.
Knowledge of harness engineering concepts to direct and optimize AI system behavior.
Nice to Have
Adaptability, Critical thinking and growing mindset
Management and collaboration skills, Verbal and written communication skills
Team contributor and care about team members
Graduate 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.
What's in it for you?
We thrive on the challenge to be our best, progressive thinking to keep growing, and working together to deliver trusted advice to help our clients thrive and communities prosper. We care about each other, reaching our potential, making a difference to our communities, and achieving success that is mutual.
A comprehensive Total Rewards Program including bonuses and flexible benefits, competitive compensation, commissions, and stock where applicable
Leaders who support your development through coaching and managing opportunities
Ability to make a difference and lasting impact
Work in a dynamic, collaborative, progressive, and high-performing team
A world-class training program in financial services
Flexible work/life balance options
Opportunities to do challenging work
Opportunities to take on progressively greater accountabilities
Opportunities to building close relationships with clients
Access to a variety of job opportunities across business and geographies
#LI-POST
#TECHPJ
Job Skills
Big Data Management, Data Mining, Data Science, Deep Learning, Machine Learning (ML), Predictive Analytics, Programming Languages
Additional Job Details
MEADOWVALE BUSINESS PARK, 6880 FINANCIAL DR:MISSISSAUGA
Mississauga
Canada
37.5
Full time
TECHNOLOGY AND OPERATIONS
Regular
Salaried
2026-06-24
2026-07-31
Note: Applications will be accepted until 11:59 PM on the day prior to the application deadline date above
Our Employment Opportunities
At RBC, we are guided by living shared values of Client First, Integrity, Collaboration, Respect and Excellence and winning together as One RBC. 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 to 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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RBC is presently inviting candidates to apply for this existing vacancy. Applying to this posting allows you to express your interest in this current career opportunity at RBC. Qualified applicants may be contacted to review their resume in more detail.
