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Senior Software Engineer; Global Security

Job in Toronto, Ontario, M5A, Canada
Listing for: 0000050007 Royal Bank of Canada
Full Time position
Listed on 2026-06-18
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software), Cybersecurity, Machine Learning/ ML Engineer
Job Description & How to Apply Below
Position: Senior Software Engineer (Global Security)

Job Description

What is the opportunity?Do you enjoy cyber security research and innovation, proactive thinking and problem solving, in a challenging and adaptive environment while constantly thinking outside of the box? If so, this opportunity is right for you!

RBC`s Security Research & Innovation team is responsible for researching threats to the organization and its clients and employees and designing solutions and techniques for countering these threats. We are a team of experienced and enthusiastic security experts, researchers, developers, and innovators that are passionate about envisioning novel solutions to complex cyber security and digital crime problems. We take ideas through the full lifecycle of research, experimentation, development, and deployment to build solutions in areas where security vendors are one step behind.

We leverage cutting edge cloud Devops, AI/ML, and security analysis technology to reduce risk to our organization, employees, and clients.

We’re looking for a Senior Software Engineer with a passion for security and a builder’s mindset — someone who thrives at the intersection of cutting-edge Python development, cloud-native architecture, and applied AI.

The right candidate combines deep engineering skills with security domain knowledge and is driven to create platforms that give defenders a decisive advantage over adversaries.
What will you do?
  • Design, build, and iterate on a custom security research platform using modern Python (FastAPI, Pydantic) and cloud-native services
  • Architect and implement scalable data pipelines that ingest, enrich, and correlate threat intelligence from diverse sources including threat feeds, data lakes, and third-party security APIs
  • Develop and integrate AI/ML capabilities — including LLM-powered analysis, RAG pipelines, and fine-tuned models — to accelerate security research workflows and surface actionable intelligence
  • Use your creative mindset to build internal tooling and techniques to counter active cyber attacks
  • Leverage cloud compute to enable high-throughput, low-latency analysis of large-scale security datasets
  • Collaborate closely with security researchers and data scientists to prototype new detection and investigation capabilities
  • Maintain engineering best practices across the platform: CI/CD, automated testing, observability (logging, tracing, alerting), and secure software development lifecycle
  • Evaluate and integrate emerging AI frameworks, foundation models, and cloud services to continuously improve platform capabilities and research velocity
  • What will you need to succeed ?
    Must Have:
  • 5+ years of hands-on software engineering experience, with the majority in Python — including async patterns, packaging, and production-grade service development
  • Proven experience designing and deploying cloud-native applications on at least one major cloud provider (AWS, GCP, or Azure), including compute, storage, networking, and IAM
  • Solid understanding of RESTful API design and experience building backend services consumed by internal tools or analysts
  • Experience building and operating data pipelines at scale — ETL/ELT, streaming or batch, with tools such as Kafka, Airflow, Spark, or cloud-native equivalents
  • Practical experience integrating AI/ML capabilities into production systems — whether LLM APIs (OpenAI, Anthropic, etc.), model inference, or ML frameworks (scikit-learn, Pytorch)
  • Strong working knowledge of containerization (Docker) and orchestration (Kubernetes or equivalent)
  • Familiarity with security concepts — threat intelligence, attack frameworks (MITRE ATT&CK), log analysis, or security tooling — sufficient to engage meaningfully with security researchers
  • Demonstrated engineering discipline: version control (Git), CI/CD pipelines, automated testing, and code review practices
  • Ability to work independently on ambiguous problems and translate loose research requirements into well-scoped engineering deliverables
  • Nice to Have:
  • Experience building platforms or tooling specifically within a cybersecurity context (SOC, DFIR, Threat Intel, Red Team support)
  • Hands-on experience fine-tuning/prompt engineering for domain-specific LLM applications
  • Familiarity…
  • Position Requirements
    10+ Years work experience
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