Staff Application Security Engineer

Censys

2d•$172,000 - $233,000•Remote

About The Position

Censys is seeking a Staff Application Security Engineer to join our Infrastructure and Operations Platform (SRE) team. In this role, you’ll own the application security strategy for how Censys builds and ships software — designing the secure paths, guardrails, and automation that let our engineers develop and deploy quickly, confidently, and securely. You’ll set technical direction across the software lifecycle, from infrastructure-as-code and container security to secure deployment workflows and the security of our AI/ML-enabled services. As a security company, we hold ourselves to the standard we help our customers achieve; this role is central to making that real. We expect all of our employees to consider customer happiness as our primary goal and to come to work every day eager to learn and educate, helping to make us a better organization every day.

Requirements

10+ years of experience in Security Engineering, DevSecOps, SRE, or related roles, with a track record of leading security initiatives that span multiple teams
Deep expertise securing Kubernetes environments, including container images, network policies, and supply chain protections (e.g., Helm, Crossplane)
Strong experience with Application Security tooling — dependency scanning, static analysis, and policy enforcement — integrated into CI/CD pipelines such as GitHub Actions and ArgoCD, and the ability to bridge engineering practices with Security Operations
Strong understanding of attacker tactics, techniques, and procedures (TTPs), and familiarity with frameworks like MITRE ATT&CK
Strong grasp of cloud services (GCP preferred), especially securing data pipelines, model hosting endpoints, and related infrastructure
Proficiency with Infrastructure-as-Code (Terraform, Crossplane, or similar) and security scanning for cloud resources
Proficiency with scripting and automation (e.g., Python, Bash)
The ability to thoughtfully participate in technical discussions and drive towards data-driven decisions amidst ambiguity and competing priorities
Strong communication skills and empathy for developer needs, with a demonstrated ability to embed secure practices without creating friction

Nice To Haves

Experience building or scaling an AppSec or DevSecOps program from early maturity, including establishing paved roads and measuring adoption
Familiarity with commercial security platforms such as Orca Security (CNAPP/cloud security posture) and Aikido Security (application security scanning) is a plus
Experience securing ML toolchains (e.g., TensorFlow, PyTorch) and familiarity with AI-specific threats such as data leakage, model inversion, prompt injection, and adversarial inputs
Hands-on experience integrating and managing Web Application Firewalls (WAF), anti-DDoS systems, and edge protection technologies
Familiarity with monitoring and observability systems (e.g., Prometheus, Grafana, OpenTelemetry) with a focus on detecting security anomalies
Familiarity with AI governance and compliance standards (e.g., EU AI Act, NIST AI Risk Management Framework)
Strong interest in harnessing AI and LLM tools as a force multiplier — using them to code smarter, iterate faster, boosting productivity and enhancing product capabilities

Responsibilities

Own and drive the AppSec/DevSecOps program roadmap across engineering, defining the strategy for embedding security into the SDLC through shift-left practices, paved roads, and automation rather than gates
Design, build, and maintain DevSecOps tooling in Kubernetes and Google Cloud Platform (GCP), including support for AI/ML workloads
Lead the integration of security into CI/CD pipelines — code scanning, secret detection, software composition analysis, and infrastructure policy enforcement — partnering with engineering teams to adopt them without friction
Deliver capabilities such as hardened service templates, secure service catalogs, and guardrails that reduce developer cognitive load and risk across the organization
Set the security architecture direction for AI/ML workflows, implementing controls around model training, deployment, and inference pipelines, including access control, artifact validation, input/output sanitization, and model provenance tracking
Partner with CorpSec on company security and compliance initiatives, owning the engineering side of the requirements by designing and implementing controls for SOC 2 and ISO27001 audit readiness, as well as improving tooling around BCDR, infrastructure policies, and service inventory accuracy
Provide technical leadership and mentorship, raising the security bar through design reviews, threat modeling, and pragmatic guidance to engineers across all teams
Participate in a shared on-call rotation with the Infrastructure and SRE teams, supporting production uptime and security incident response readiness