Job Description
What is the opportunity?
As a Lead 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.
What will you do?
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.
Champion best practices in AI safety, privacy, regulatory compliance, and autonomous system guardrails, including model monitoring, fallback mechanisms, and secure deployment in regulated environments.
What do you need to succeed?
Must Have
6+ years of software engineering experience with Python, SQL, pyspark and at least one of React, Angular, and Vue.js.
Demonstrated hands-on experience deploying LLMs, RAG systems, agent orchestration frameworks (e.g., LangChain, CrewAI, AutoGen), or agentic AI into production, including vector database configuration (pgvector, Milvus, Pinecone, FAISS), and context engineering for autonomous workflows.
Hands-on experience deploying ML/AI solutions (LLMs, RAG, classical ML) into Production, including model fine-tuning 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, FastAPI, Django.
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 deliver robust, production-ready autonomous AI solutions and platforms, drive continuous improvement, advocate for safety and privacy-by-design, and communicate effectively with technical and business stakeholders.
Nice to Have
Experience fine-tuning LLMs (e.g., LoRA, PEFT), prompt engineering, and large-scale model deployment using HuggingFace, DeepSpeed, Triton, or ONNX.
Familiarity with AWS cloud environments services (Lambda, SageMaker, Bedrock, etc).
Familiarity with workflow orchestration platforms Airflow, RunAI, N8N, Helios. Understanding of modern observability stacks (Grafana, Prometheus, OpenTelemetry) and secure coding practices (SAST/DAST)
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
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.
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Job Skills
Big Data Management, Data Mining, Data Science, Deep Learning, Machine Learning, Predictive Analytics, Programming LanguagesAdditional Job Details
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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.
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Expand your limits and create a new future together at RBC. Find out how we use our passion and drive to enhance the well-being of our clients and communities at jobs.rbc.com.