Senior Infrastructure Engineer - Toronto

About DataVisor DataVisor is the world's leading AI-powered Fraud and Risk Platform that delivers the best overall detection coverage in the industry. With an open SaaS platform that supports easy consolidation and enrichment of any data, DataVisor's fraud and anti-money laundering (AML) solutions scale infinitely and enable organizations to act on fast-evolving fraud and money laundering activities in real time. Its patented unsupervised machine learning technology, advanced device intelligence, powerful decision engine, and investigation tools work together to provide significant performance lift from day one. DataVisor's platform is architected to support multiple use cases across different business units flexibly, dramatically lowering total cost of ownership compared to legacy point solutions. DataVisor is recognized as an industry leader and has been adopted by many Fortune 500 companies across the globe. Our award-winning software platform is powered by a team of world-class experts in big data, machine learning, security, and scalable infrastructure. Our culture is open, positive, collaborative, and results-driven. Come join us! Role Overview Our infrastructure team runs the platform that makes real-time fraud detection possible, and writes much of the software that runs on it. You will own production infrastructure end to end: Kubernetes clusters on AWS, the streaming and data systems behind detection, and the tools and services that keep them reliable. You will also design and build backend and platform code alongside the engineering teams. Requirements What you'll do Design, operate and scale Kubernetes (EKS) clusters for multi-tenant and customer-dedicated deployments: Helm, upgrades, autoscaling, troubleshooting. Build AWS infrastructure as code with Terraform (VPC, IAM, EC2, EKS, S3) and keep environments reproducible. Run and tune the data systems detection depends on: Kafka, Flink, Spark, ClickHouse and MySQL, covering capacity, performance and reliability. Own observability with Prometheus, Grafana and Loki. Define SLOs, lead incident response and run on-call. Develop production software in Java, Go or Python: platform services, internal tools, deployment automation and CI/CD pipelines. Help design distributed real-time systems with the platform team, for low-latency decisioning at scale. Lead security and reliability practices: access control, secrets, backups, disaster recovery, and SOC 2 / PCI controls. Drive cloud cost optimization across compute and big-data workloads. Mentor junior engineers and set infrastructure standards. What you'll bring 5+ years in infrastructure, SRE, DevOps or platform engineering on production systems. Hands-on experience running Kubernetes in production. Strong AWS experience and infrastructure as code (Terraform or CloudFormation). Monitoring, alerting and on-call experience with Prometheus/Grafana or similar tools. Solid programming skills in Java, Go or Python, with experience shipping production code, not only scripts. Experience running at least one distributed data system (Kafka, Flink, Spark, ClickHouse or MySQL). A degree in Computer Science, Computer Engineering, Electrical Engineering or a related field, or equivalent experience. Nice to have Fraud, risk, payments or banking infrastructure; SOC 2 or PCI environments. Low-latency streaming or real-time decisioning platforms. Multi-region, multi-tenant or customer-hosted (private) SaaS deployments. FinOps or cloud cost reduction with measurable results. Internal tooling built with LLMs, or AI-assisted operations. Benefits Compensation: Annual salary range of CAD $120,000 – $150,000, commensurate with experience. Health Insurance, including (Extended Health Care, Vision Care, and Dental Care) Life Insurance, Accidental Insurance Retirement Savings Plan Paid Vacation