Senior Security Engineer, Network – Zero Trust

Sezzle

. Own east-west segmentation across Kubernetes clusters using default-deny micro-segmentation and identity-bound paths .

Posted 11/3/2026full-timeRemoteSenior💰 $5,000 - $9,500 per monthWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in Kubernetes networking, AWS networking, and security engineering, with a strong focus on implementing micro-segmentation and mTLS for secure service connections. Proficient in infrastructure as code and automation, with a solid understanding of compliance standards such as PCI DSS.

Highest-signal resume keywords

Kubernetes NetworkingAWS NetworkingMTLS ImplementationInfrastructure As CodeSecurity Engineering

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

KubernetesAWSMTLSTerraformHelmGoPythonBashPacket Capture AnalysisPCI DSS

Tools & Technologies

SIEMZTNACiliumEBPFHubbleAI ToolingPolicy As CodeAdmission ControlIDS/IPSSOC 2

Industry Keywords

Micro-SegmentationNetwork ControlsCloud ProductionService MeshRegulated Industry ExperienceTraffic-Flow DesignIncident ResponseDrift DetectionNetwork DetectionCardholder-Data Environment

Tech Stack

Tools & technologies

AWSCloudDNSKubernetesPythonTerraformGo

About the role

Key responsibilities & impact

Own east-west segmentation across Kubernetes clusters using default-deny micro-segmentation and identity-bound paths
Design and roll out mutually authenticated, encrypted service-to-service connections using mTLS
Maintain a continuously reconciled map of VPC peerings, tunnels, cross-account links, and public entry points
Implement and enforce production and cardholder-data-environment boundaries and conduct segmentation testing
Partner with IT to evaluate and deliver per-application private access through ZTNA
Own network telemetry, including east-west and north-south flow logs, and feed it to the SIEM
Own cluster admission control, infrastructure-as-code enforcement, and automated drift detection and remediation
Build containment capabilities for isolating workloads or segments during lateral-movement incidents
Participate in threat modeling, traffic-flow design reviews, incident response, and on-call rotation
Write policies, tooling, and rollout automation; coordinate changes across other teams' services
Use and build AI-assisted engineering workflows for flow analysis, policy generation, and drift review
Report to the Director of Information Security and collaborate with security platform, detection and response, platform, and IAM teams

Requirements

What you’ll need

6+ years of experience in security, network, platform, or infrastructure engineering, with hands-on ownership of network controls in cloud production environments
Deep practical Kubernetes networking knowledge: CNI, NetworkPolicy semantics, DNS, ingress/egress, and experience rolling segmentation out on live clusters without outages
Strong AWS networking knowledge: VPCs, subnets, security groups, peering, Transit Gateway, PrivateLink, load balancers, and flow logs
Hands-on experience with mTLS and service-to-service authentication
Infrastructure as code using Terraform and Helm or equivalents, through merge requests and CI
Ability to write code in Go, Python, or Bash for tooling and automation
Ability to investigate with packet captures, flow logs, and system-level data
Working knowledge of PCI DSS network requirements, including segmentation, cardholder-data environment scoping, and segmentation testing
Demonstrated current use of AI tooling such as Claude Code, Codex, Cursor, or custom LLM integrations
Preferred: Cilium/eBPF, Hubble or equivalent, fleet-scale mTLS, certificate lifecycle, service mesh, SPIFFE/SPIRE, AI-assisted workflows, ZTNA, policy-as-code, admission control, network detection, IDS/IPS, SOC 2, FFIEC-style expectations, and regulated-industry experience

Benefits

Comp & perks

Competitive gross salary of $5,000–$9,500 USD per month, based on experience
Culture including skilled musicians, yogis, cyclists, chefs, golfers, dog-lovers, and rock-climbers
Open-source-focused engineering environment
AI-assisted engineering workflows and tools