Senior AI Engineer (Global Security)

RBC•Toronto, ON

2d•Hybrid

About The Position

We're looking for a talented Senior AI Engineer (Global Security) with deep expertise in Python programming and applied AI systems who will drive the design and implementation of sophisticated agentic AI solutions and Large Language Model (LLM) applications. You will immediately contribute to existing MCP server deployments and design next-generation security automation capabilities. This is a unique opportunity to architect AI technologies that directly impact RBC's security posture and enhance developer experience across the organization. At RBC Global Security, you'll be joining a team that builds AI solutions to reduce vulnerabilities across the organization and enhance developer experience. The team has access to rich datasets and computational resources to support development in agentic AI systems, LLM applications, and intelligent security platforms. The role involves strategic design, hands-on development, mentorship, and execution to ensure objectives are accomplished with excellence.

Requirements

5+ years software development experience, with 2+ years in AI/ML; expert in Python for production systems
Deep expertise designing and deploying NLP/Generative AI applications; proven track record with vector databases, LLMs, and RAG pipelines
1-2+ years hands-on experience with Anthropic Claude API (function calling, tool use, extended context) OR equivalent production LLM experience (OpenAI/Cohere)
Expert in building and deploying MCP servers for enterprise data integration; proven implementation of AI agent architectures with tool-calling capabilities
Advanced proficiency with AI frameworks (FastAPI, LangChain, LangGraph) and Python libraries (NumPy, Pandas, scikit-learn)
Advanced prompt engineering expertise: multi-step reasoning, prompt caching strategies, cost optimization, Anthropic Skills framework, and agent orchestration patterns
Solid understanding of cloud platforms (OCP, Azure, AWS), web services (SOAP/REST), Git/GitHub Actions, Docker, databases (SQL/NoSQL), middleware (Kafka/Redis), and JSON-RPC protocols
Strong cybersecurity practices and secure coding; experience implementing authentication/authorization for AI service integrations

Nice To Haves

React and JavaScript experience
MLOps tools, service mesh architectures, API gateway patterns, and cloud certifications (AWS/Azure)
Familiarity with SIEM integration patterns, security incident management workflows, and monitoring tools
Background in NLP/ML research
Constitutional AI principles, responsible AI development, and bias testing practices

Responsibilities

Design, develop, and optimize sophisticated NLP and Generative AI applications using Python; architect scalable agentic AI systems, RAG pipelines, and LLM integrations leveraging vector databases, embeddings, and advanced prompt engineering
Design and implement Model Context Protocol (MCP) servers for enterprise data integration; build custom MCP servers connecting LLM applications to internal databases, APIs, and knowledge bases; contribute to existing MCP deployments developing new features and optimizations
Develop and maintain Anthropic Claude-based solutions leveraging extended context windows, advanced reasoning, tool-calling architectures, and agent orchestration for enterprise system integration
Design and deploy robust deployment pipelines to cloud platforms (OpenShift, Azure, AWS); containerize applications using Docker; build CI/CD workflows with GitHub Actions; manage MCP server infrastructure with proper authentication, security, and monitoring
Mentor junior developers on AI architecture patterns, MCP implementations, and best practices; conduct code reviews with focus on security, performance, and maintainability
Partner with security architects, product teams, data engineers, and business stakeholders to translate requirements into innovative AI solutions

Benefits

bonuses
flexible benefits
competitive compensation
commissions
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
Flexible work/life balance options
Opportunities to do challenging work
Opportunities to take on progressively greater accountabilities
Access to a variety of job opportunities across business