Senior Application Security Engineer, AI & Product Security

Senior Application Security Engineer, AI & Product Security

Artera is seeking a hands‑on Senior Application Security Engineer, AI & Product Security to work alongside our AI builders and Systems Engineers to threat‑model agentic and LLM‑powered features, harden PHI/PII‑handling workflows, and ship the "paved road" tooling (secure SDLC guardrails, prompt/agent‑identity patterns, SAST/DAST/SCA in CI/CD) that keeps innovation fast and safe. This is a frontier role in which you will translate policy into code, build guardrails for agent identity and prompt/output filtering, and give our team the logging, scanning, and safe tool‑use patterns.

The role is based in our Seattle, WA office and supports federal‑facing systems and enterprise security functions.

Candidates must meet eligibility for a government background check and follow strict data protection, access control, and incident response protocols. Familiarity with regulatory frameworks is expected; ongoing compliance training and evidence‑based documentation may be required.

• AI Threat Modeling
  :
  Threat‑model agentic and LLM‑powered features end‑to‑end: data ingress/egress, agent identity, tool‑use boundaries, and the unique risks that come with frontier AI work
• Paved Road Tooling
  :
  Build the secure SDLC paved road — secure SDLC guardrails, prompt/agent identity patterns, secrets management, PHI/PII redaction patterns
• Security Gates
  :
  Embed SAST, DAST, SCA, and infrastructure scanning into CI/CD so security gates are part of the pipeline, not an afterthought
• AI Monitoring Strategy
  :
  Identify and pilot an AI monitoring tool to fill the gap our current tooling (Zscaler) doesn't cover
• Policy & Practice
  :
  Translate existing security policy into safe tool‑use patterns for the Artera Primitives team, Systems Engineers, and other AI Builder squads
• Cross Functional Partnership
  :
  Partner cross‑functionally with Dev Ops, Systems Engineering, and the AI builder teams — meeting AI Builders and engineers in the middle and finding the secure path forward, not the "no" path
• Security Ownership
  :
  Own AWS identity and access management patterns, secrets management, and security tooling decisions in our AWS environment. Collaborate with System Engineers / Dev Ops on implementation.
• Security Framework Application
  :
  Apply frameworks like MITRE ATT&CK, MITRE ATLAS, OWASP Top 10, and OWASP LLM Top 10 to architectural decisions.

• App Sec Tenure
  : 6–10 years in Application Security, with a hands‑on engineering orientation
• LLM & Agent Security
  :
  Demonstrable experience with LLM and agent security — OWASP LLM Top 10, MITRE ATLAS, prompt/output filtering, agent identity, and tool‑use risk
• Threat Modeling Expertise
  :
  You’ve built end‑to‑end threat models for production platforms and translated them into corrective controls
• Pipeline Scanning Tools
  : SAST, DAST, and infrastructure scanning tools in production CI/CD environments
• Shift‑Left Security Experience
  :
  Taking policy, codifying it as infrastructure‑as‑code (Terraform), and gating CI/CD pipelines on security findings
• Cloud Depth
  :
  Significant AWS experience (GCP or Azure background acceptable; AWS is learnable, but cloud depth is required)
• Regulated Environment Experience
  :
  Background in regulated environments — healthcare (HIPAA/HITRUST), federal (FedRAMP), or fintech (PCI)
• Collaborative Communicator
  :
  Strong cross‑functional communicator; able to partner with engineers and AI builders, find the secure path together.

• Agentic AI Modeling
  :
  Direct experience threat‑modeling agentic AI systems (rare — but if you have it, you're the cherry on top)
• Agentic Platform Exposure
  : AWS Agent Core, MCP, or similar agent‑platform exposure
• Growth Stage AI Experience
  :
  Experience at a growth‑stage company (~50–500 people) that has already adopted agentic AI
• Fintech to Agentic Path
  :
  Background in fintech transitioning into agentic systems (a common path into this kind of work today)
• AI Monitoring Tool Ownership
  :
  Past ownership of an AI monitoring tool rollout or evaluation

Compensation
: $146,000 – $175,000 a year (based on level of experience and geographic tier). This position also comes with equity and a variety…