Lead Ai/ml Engineer, (global Security)

Royal Bank of Canada

Toronto, Canada
Base: not specified; bonus/equity: bonuses + commi...
Hybrid
Python and java/typescript/go programming
Deployment of llms and rag systems
Agent orchestration frameworks (langchain, crewai, autogen)
As the Senior Lead AI/ML Engineer, you will build RBC’s next-generation platform for autonomous and semi-autonomous AI in Risk & Security to automate complex controls and accelerate regulatory readiness

Job Summary

  • As the Senior Lead AI/ML Engineer, you will build RBC’s next-generation platform for autonomous and semi-autonomous AI in Risk & Security to automate complex controls and accelerate regulatory readiness.
  • You will architect, develop, and deploy enterprise AI agentic solutions, lead cross-functional teams, and champion best practices in AI safety, privacy, and regulatory compliance.
  • RBC offers a comprehensive Total Rewards Program including bonuses, flexible benefits, competitive compensation, leadership development, and opportunities for impactful and challenging work.

Matching Summary

As the Senior Lead AI/ML Engineer, you will build RBC’s next-generation platform for autonomous and semi-autonomous AI in Risk & Security to automate complex controls and accelerate regulatory readiness.

Salary

Base: Not specified; Bonus/Equity: Bonuses and commissions mentioned; Benefits: Flexible benefits and stock where applicable

Skills & Requirements

Must-have

  • Python and Java/TypeScript/Go programming
  • Deployment of LLMs and RAG systems
  • Agent orchestration frameworks (LangChain, CrewAI, AutoGen)
  • Vector database configuration (pgvector, Milvus, Pinecone)
  • MLOps/DevOps with Kubernetes and CI/CD pipelines
  • Cloud and on-premises development (AWS, Azure)
  • Data engineering with Spark, Databricks, Airflow

Nice-to-have

  • Fine-tuning LLMs with LoRA and PEFT
  • Prompt engineering and large-scale model deployment
  • Distributed ML and monitoring frameworks (Ray, SageMaker)
  • Real-time data pipelines (Kafka, Kinesis)
  • Enterprise GRC data schema familiarity
  • Dual-cloud or hybrid environment experience
  • Advanced security tooling and observability stacks
  • Regulatory frameworks knowledge (NIST, ISO, SOX)

Key Requirements

  • Bachelor’s degree in Computer Science or related field
  • 6+ years software engineering experience
  • Experience deploying production-grade autonomous AI solutions
  • Proficiency with Python and at least one of Java, TypeScript, or Go
  • Experience with vector databases and context engineering
  • Knowledge of MLOps/DevOps and cloud/on-prem environments

Work Rights

Not specified

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