Staff AI Engineer (Global Security)

RBC•Toronto, ON

3d•Onsite

About The Position

We're looking for an experienced Staff AI Engineering (Global Security) expert who will bring technical leadership and subject-matter expertise in designing and implementing agentic AI systems and Large Language Model (LLM) applications. You will lead the development of next-generation AI technologies, establish technical standards across the team, and work with a team of passionate individuals committed to bringing advanced AI to enterprise security. 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 and massive datasets and computational resources to support development in agentic AI systems, LLM applications, and intelligent security platforms. The role involves strategic technical leadership, 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-level Python proficiency for production systems
Deep expertise designing and deploying NLP/Generative AI applications; proven track record with vector databases, LLMs, and RAG pipelines
Expert-level experience with Model Context Protocol (MCP) servers for enterprise data integration; proven track record implementing complex multi-system AI architectures
1-2+ years hands-on experience with Anthropic Claude API and SDK (function calling, tool use, extended context) OR equivalent production LLM experience
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
Demonstrated experience leading or architecting large-scale AI/ML projects from conception through production; ability to make high-impact design decisions with long-term implications

Nice To Haves

MLOps tools, service mesh architectures, API gateway patterns, and cloud certifications (AWS/Azure)
Familiarity with SIEM integration patterns and security incident management workflow
Understanding of Docker and other containerization platforms

Responsibilities

Design, develop, and maintain sophisticated NLP and Generative AI applications in 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
Build and maintain 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
Develop AI-driven security tools and applications for scalability and resiliency; integrate applications with SIEM systems for alerting and reporting
Establish technical direction and architectural standards for MCP server development, AI framework selection, and prompt engineering practices across Global Security; lead architectural reviews of team implementations
Lead the design of complex, multi-system AI integrations; architect for scalability, resilience, and cost optimization at enterprise scale
Define AI strategy in collaboration with product leadership; translate business objectives into technical roadmaps, prioritization, and architectural decisions
Perform root-cause analysis for production issues and provide solutions; manage risks, assumptions, and constraints; communicate to appropriate parties

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