About the Role We're hiring a Member of Technical Staff (Security Engineer) to own security engineering at Hark. You'll threat-model our systems, harden our cloud and product infrastructure, build detection capabilities, and lead incident response when things go wrong. As AI agents become a core part of our product, you'll also be on the frontier of LLM and agent security - a space with very few established playbooks.
This role is hands-on; you'll be building and operating, not managing or auditing.
Responsibilities- Threat-model Hark's infrastructure, product, and agent/LLM attack surfaces.
- Harden cloud infrastructure (EKS, IAM, network access paths) and review IaC for misconfigurations and vulnerabilities.
- Build and maintain detection and alerting pipelines; lead triage and containment during incidents.
- Partner with engineering to embed security into the development lifecycle.
- Define and evolve Hark's security posture as the product and team scale.
Requirements- 4-8 years of hands-on security engineering experience.
- Deep fluency in cloud security (AWS/GCP, IAM, Kubernetes, network hardening).
- Experience with detection engineering and incident response - you've triaged real alerts and contained real incidents.
- Ability to read and review infrastructure-as-code (Pulumi, Terraform, or similar) for security issues.
- Genuine curiosity about LLM and agent security - this is new territory and we want someone excited to figure it out.
Bonus Qualifications- Experience at a cloud security company (Wiz, Orca, Datadog, Snyk) or a security-forward startup (Stripe, Figma, Ramp, Netflix).
- Familiarity with zero-trust networking (Tailscale, Cloudflare, HashiCorp Vault).
- Prior exposure to AI/agent security threat modeling.
CompensationThe US base salary range for this full-time position is between $150,000 - $300,000 annually.
The pay offered for this position may vary based on several individual factors, including job-related knowledge, skills, and experience. The total compensation package may also include additional
