Lead AI​/ML Engineer; Global Security

Position: Lead AI/ML Engineer, (Global Security)

Job Description What is the opportunity? As the Senior Lead AI/ML Engineer, you will build RBC’s next-generation platform for autonomous and semi-autonomous AI in Risk & Security. You will drive the full engineering lifecycle to create self-directed, context-aware AI agents and workflows that operate with minimal human intervention leveraging your expertise in large language models (LLMs), generative AI, machine learning, cloud-native development, and data pipelines.

You’ll work with a dedicated GPU and multi-cloud stack to deliver highly scalable, production-grade AI solutions that automate complex controls, accelerate regulatory readiness, and set new standards for operational excellence and security. What will you do? • Architect, develop, and deploy enterprise AI agentic solutions using Python, Java, or TypeScript to automate risk, audit, and cybersecurity processes at scale. • Lead end-to-end delivery of LLMs and RAG systems (OpenAI, Cohere, Claude, Llama), vector search (pgvector, Milvus, Pinecone), and advanced context engineering pipelines (Lang Chain, Semantic Kernel) to ensure AI actions are context-aware, secure, and aligned with real-time enterprise data. • Design and orchestrate autonomous agent workflows for decision-making, control testing, auto-remediation, anomaly detection, and continuous assurance, leveraging frameworks such as Lang Graph, CrewAI, or Auto Gen. Engineer and optimize data pipelines and context layers (Spark, Databricks, Airflow, SQL/No

SQL, FastAPI, Graph

QL) to deliver high-quality, relevant context for AI-driven decisions and automation. • Deliver, document, and maintain robust SDKs, APIs, and reusable components for risk, regulatory, and security AI automation across cloud and on-premise environments (AWS, Azure, on-prem GPU). • Integrate AI solutions with enterprise systems and platforms, including GRC, Service Now IRM, Dev Ops (Docker, Kubernetes, Git Hub Actions, Jenkins), and production monitoring/observability tools. • Champion best practices in AI safety, privacy, regulatory compliance, and autonomous system guardrails, including model monitoring, fallback mechanisms, and secure deployment in regulated environments (NIST, SOX). • Collaborate and lead cross-functional technical teams, influence platform strategy, mentor engineers, share knowledge, and maintain high-quality technical documentation for both internal and external stakeholders. What do you need to succeed? Must Have • Bachelor’s degree (or equivalent) in Computer Science, Software Engineering, or a related field. 6+ years of software engineering experience with Python and at least one of Java, TypeScript, or Go. • Demonstrated hands-on experience deploying LLMs, RAG systems, agent orchestration frameworks (e.g., Lang Chain, CrewAI, Auto Gen), or agentic AI into production, including vector database configuration (pgvector, Milvus, Pinecone, FAISS), and context engineering for autonomous workflows. • Proficient with MLOps/Dev Ops, containers, Kubernetes, CI/CD pipelines (Docker, Git Hub Actions, Argo CD, Jenkins), and cloud/on-prem development (AWS, Azure) at enterprise scale. • Strong data engineering and integration skills with Spark, Databricks, Airflow, SQL (Snowflake, Postgres), No

SQL (Mongo

DB), unstructured data (blobs/OCR), and API design (REST, Graph

QL, gRPC, FastAPI). • Ability to deliver robust, production-ready autonomous AI solutions and platforms, drive continuous improvement, advocate for safety and privacy-by-design, and communicate effectively with technical and business stakeholders. Nice to Have • Experience fine-tuning LLMs (e.g., LoRA, PEFT), prompt engineering, and large-scale model deployment using Hugging Face, Deep Speed, Triton, or ONNX. Familiarity with distributed ML/monitoring frameworks (Ray, Sage Maker), real-time pipelines (Kafka, Kinesis), and enterprise GRC data schemas (Service Now IRM, Archer). • Experience with dual-cloud or hybrid environments, advanced security tooling (SAST/DAST, Vault/KMS), and modern observability stacks (Grafana, Prometheus, Open Telemetry). Understanding of regulatory frameworks and IT controls (NIST 800-53, ISO 27001, SOX/ITGC automation). What’s in it for you? We thrive on…