AI Engineer - Quantitative Technology Services
Description For AI Engineer - Quantitative Technology Services
RBC Capital Markets is seeking an AI Engineer to join their Quantitative & Technology Services (QTS) team, specifically within the Data AI and Research Technology (DART) division. This role presents an exciting opportunity to work at the intersection of finance and artificial intelligence, building cutting-edge AI solutions for Investment Research, Banking, Sales and Trading.
The position involves working with modern AI technologies and frameworks including FastAPI, LangChain, LangGraph, and Cohere, while integrating with enterprise-scale data sources like Snowflake, Azure Blob, and S3. You'll be part of a team focused on GenAI initiatives, creating systems that orchestrate models, tools, and data into intelligent, context-aware pipelines.
QTS is a cross-asset development organization that delivers innovative solutions for RBC Capital Markets in partnership with Technology & Operations. The team leverages Digital, Data, and AI to deepen client relationships and supports various aspects of the business including Lending & Finance, Advisory & Origination, and Client Trading & Market Making.
The role offers competitive compensation ranging from $100,000 to $135,000, along with comprehensive benefits including bonuses, flexible benefits, and stock options where applicable. RBC provides a collaborative and progressive work environment with opportunities for professional development and coaching.
As an AI Engineer, you'll be responsible for building robust backend services, developing GenAI applications, and contributing to systems that enable intelligent routing of prompts and dynamic tool execution. The ideal candidate should have strong Python development skills, experience with container technologies, and familiarity with LLM frameworks and cloud platforms.
RBC is Canada's largest bank and one of the largest globally, with approximately 84,000 employees serving over 16 million clients across 36 countries. The company maintains a strong commitment to innovation and technological advancement while fostering an inclusive workplace that values diverse perspectives.
Responsibilities For AI Engineer - Quantitative Technology Services
- Build robust backend services and APIs using Python (FastAPI, asyncio) for GenAI workflows and LLM-based systems
- Develop and maintain GenAI applications using tools like LangChain, LangGraph, and Cohere
- Contribute to systems that enable intelligent routing of prompts, dynamic tool execution, and seamless model-data integration
- Write clean, modular code for model integration, semantic search, and multi-step agent workflows
- Package and deploy applications using Docker and Kubernetes
- Collaborate with data engineers, AI scientists, and infra teams to ship end-to-end features
Requirements For AI Engineer - Quantitative Technology Services
- Strong backend development skills in Python with FastAPI and async programming
- Experience deploying services with Docker and Kubernetes in a cloud environment
- Familiarity with LLM APIs (OpenAI, Cohere) and how to build prompt-based applications
- Solid understanding of LangChain, LangGraph, or other LLM orchestration frameworks
- Comfortable writing and debugging PySpark jobs and working with Delta Lake in Databricks
- Experience working with APIs, JSON schemas, structured/unstructured data, and task automation
- Experience working with Git workflows, CI/CD, and container-based deployments
- Degree in Computer Science or Engineering
Benefits For AI Engineer - Quantitative Technology Services
- Comprehensive Total Rewards Program including bonuses and flexible benefits
- Competitive compensation and stock where applicable
- Leaders who support your development through coaching
- Flexible work/life balance options
- Work in a dynamic, collaborative, progressive team
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