Senior Security Engineer, Network & Zero Trust

Role overview Lead hands-on engineering for network security and zero-trust controls across Kubernetes clusters and cloud environments. The work centers on ensuring that connections are explicitly authorized, tied to verified service identities, observable, and managed through reviewed code, while introducing controls safely across teams’ services.

Responsibilities - Design and maintain default-deny network segmentation for workloads in Kubernetes, using observed traffic to shape explicit allow rules. - Roll out encrypted, mutually authenticated service-to-service connections and support identity-based authorization. - Continuously map cloud network paths, including peerings, tunnels, cross-account links, and public entry points. - Enforce boundaries around production and cardholder-data systems, review network exposure, and conduct segmentation tests with security colleagues. - Improve private, application-specific access for engineers and operators, and provide flow telemetry that helps answer who communicated with what and when. - Manage admission controls and network configuration as code, and build automation for policy generation, flow analysis, and drift review.

Requirements - At least six years of relevant experience, with the senior-level engineering judgment to own a network security program. - Practical experience with Kubernetes network policies and cloud networking, including AWS environments. - Ability to implement service identity and mutual TLS, infrastructure-as-code controls, and network observability. - Experience introducing security controls across teams through measured, staged rollouts. - Strong engineering skills for writing policies, tooling, and automation, and for troubleshooting complex network paths.

Nice to have - Experience in fintech, payments, buy now, pay later, or another regulated environment. - Familiarity with Kubernetes admission controls, zero-trust network access, and security information and event management workflows. - Experience using or building AI-assisted engineering workflows.

Benefits and work setup - The listing describes the position as remote and full-time. - Gross compensation is listed as USD $5,000–$9,500 per month, depending on experience.