As a Senior AI Application Developer at RBC, you will help build the next generation of ML, GenAi autonomous and semi-autonomous AI platform and solutions for Cyber, Fraud, Risk & Security. You’ll work alongside experienced engineers to design, develop, and deploy production-grade AI and ML systems, gaining exposure to large language models, machine learning, data engineering, and modern cloud technologies. With access to advanced AI tools and a collaborative environment, you’ll contribute to projects that drive detective/preventive controls, automation, increase operational efficiency, and support regulatory compliance.

• Design, build, and deploy robust scalable backend services for Agentic AI applications build using Python, LangChain, LangGraph, and related frameworks.
• Build AI solutions using LLMs and RAG systems (OpenAI, Cohere, Claude, Llama), vector search (pgvector, Milvus, Pinecone), and advanced context engineering pipelines (LangChain, Semantic Kernel) to ensure AI actions are context-aware, secure, and aligned with real-time enterprise data.
• Deploy, manage, and optimize ML/Agentic applications on OpenShift Container Platform (OCP), Amazon Elastic Kubernetes Services (EKS) using Helios on Actions CI/CD pipeline.
• Apply and advocated for best practices in secure coding and MLOps CI/CD automation (Docker, Kubernetes, OpenShift, GitHub Actions, Jenkins), traceability (Langfuse) and observability (Prometheus, Grafana).
• Develop and deploy APIs (REST, GraphQL, FastAPI, gRPC) ensuring high availability, scalability, resilience, and security.
• Engineer and maintain scalable data pipelines and workflows using PySpark, SageMaker, Airflow, JupyterHub, RunAI.
• Contribute to code reviews, collaborate with data scientists and engineers, front and backend engineers and ML engineers, and maintain clear technical documentation.

Must Have

• Bachelor’s degree (or equivalent experience) in Computer Science, Software Engineering, or a related field.
• 2–4 years of software engineering experience with Python, SQL; familiarity with PySpark is an asset.
• Hands-on experience deploying ML/AI solutions (LLMs, RAG, classical ML) into Production, including model fine-tuning and vector database use (pgvector, Milvus, Pinecone) and MLOps using PyTorch, TensorFlow, or HuggingFace.
• Strong Experience building data pipelines and APIs with Spark, Databricks, Airflow, SQL (Snowflake, Postgres), and NoSQL (MongoDB); experience with REST, GraphQL or FastAPI.
• Strong experience with modern MLOps/DevOps: Docker, Kubernetes, CI/CD pipelines (Github Actions, Helios), and Cloud/On-prem platforms (OCP, AWS, on-prem GPU etc.)
• Ability to independently deliver complex features and prototypes within aggressive timelines and contribute to team best practices.

Nice to Have

• Experience working with LLMs, RAG frameworks (LangChain, Semantic Kernel), or vector databases (pgvector, Milvus, Pinecone), LLM fine-turning (LoRA, PEFT), prompt-engineering, Model Context Protocol (MCP) and large-scale model deployment (HuggingFace, DeepSpeed, ONNX)
• Familiarity with AWS cloud environments services (Lambda, SageMaker, Bedrock, etc).
• Familiarity with workflow orchestration platforms Airflow, RunAI, N8N, Helios.
• Understanding of monitoring tools (Prometheus, Grafana), secure coding practices (SAST/DAST).

Job Skills

Apache Airflow, AWS AI Services, Back-End Development, Deep Learning, Docker (Software), Generative AI, Grafana, Machine Learning, Prometheus (Software), PySpark, Python (Programming Language), Red Hat OpenShift

Additional Job Details

16 YORK ST:TORONTOTorontoCanada37.5Full timeTECHNOLOGY AND OPERATIONSRegularSalaried2025-10-142025-12-05

Note: Applications will be accepted until 11:59 PM on the day prior to the application deadline date above

Inclusion and Equal Opportunity Employment

At 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.