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Salary: USD 180,000 - 300,000 / annual
Listen Labs is hiring a Member of Technical Staff in Application Security to build security into their AI-native product from the ground up. The role is for an engineer who writes production code and ships real fixes, not one who audits from the outside.
Listen Labs operates an AI-moderated video interview platform at scale, conducting thousands of parallel interviews and surfacing human preference signals to customers (including 15% of Fortune 100 companies). The company is backed by $100M in funding from Ribbit Capital, Sequoia, Conviction, and Pear VC, with 15x annualized revenue growth since launch.
Key responsibilities include:
- Securing the database of millions of voice, face, and device-linked profiles through encryption, access boundaries, retention policies, and abuse resistance built into the product.
- Designing and maintaining multi-tenant isolation across ListenLabs staff, customer admins, and study participants with different privilege levels.
- Threat-modeling AI-native attack surfaces including prompt injection, data exfiltration through model outputs, tool and agent permissions, and LLM-specific failure modes.
- Securing the Human API as it integrates with Slack, Linear, IDEs, and coding agents through authentication, authorization, and programmatic/agentic caller design.
- Building security engineering infrastructure: secure-by-default libraries, SAST/DAST/SCA scanning, secrets scanning in CI, dependency hygiene, and fast feedback loops.
- Reviewing architecture and pull requests alongside product engineers, often writing fixes directly.
You'll work independently with one meeting per week in a hypergrowth environment. The team includes serial entrepreneurs, former founders (30%+ of staff), and talent from Google, Meta, Tesla, Amazon, Jane Street, and top-tier consulting firms.
Requirements:
- Strong engineering fundamentals: comfortable reading and writing production code in modern backend stacks (TypeScript, Terraform mentioned), junior-level or better development skills.
- Deep application security knowledge: authentication/authorization (OAuth/OIDC, sessions, RBAC), cloud/infrastructure security, secrets management, secure API design, common vulnerability classes.
- Ability to understand system design and failure modes; knowledge of OWASP Top 10 as design patterns, not checklists.
- Proven ability to ship security fixes end-to-end, not just identify issues.
- Strong written communication for async work and complex technical explanations.
- Curiosity about AI security and LLM failure modes (prior LLM security experience is a plus, not required).
- Problem-solving mindset: scoping work independently, thinking about customer trust, owning decisions.
