Member of Technical Staff, Application Security

📋 Job Overview

We're hiring an engineer who builds security into a complex AI-native product, not one who audits it from the outside. You write real code, ship real fixes, and understand how systems are built well enough to know exactly how they break. Our platform runs AI-moderated video interviews at massive scale, finding the right people from a network of millions. What used to take research teams weeks per study, we do in hours. Every interview feeds a human preference model, exposed to the world through the Human API. AI agents will call Listen from Slack, Linear, IDEs, and coding agents to ask what humans actually want. The trust people place in that signal is everything, and security is how we earn it.

🏢 About ListenLabs

World-Class Team: Founded by serial entrepreneurs, Alfred (Bemlo, YC W22) and Florian (IOI medalist, ICPC World Finalist), and built with talent from Google, Meta, Tesla, Amazon, Jane Street, and X, alongside Bain, Goldman Sachs, McKinsey, and Sequoia-backed startups like Applied Intuition, Scale AI, and Rippling. Over 30% of our team are former founders. Hypergrowth: Since launching, Listen has grown annualized revenue 15x and completed over 2 million interviews, backed by $100M in total funding led by Ribbit Capital, with Sequorita, Conviction, and Pear VC participating. Traction: Already serving 15% of Fortune 100s, with enterprise wins and expansions across Anthropic, Microsoft, Nestlé, Perplexity, Sweetgreen, and more.

🎯 The Role

You'll help design the protections for the voice, face, and device-linked profiles for millions of people. You'll ensure multi-tenant isolation, threat-model AI-native attack surfaces, secure the Human API, and build a security engineering platform. You'll also review architecture and pull requests alongside engineers.

✅ Key Responsibilities

• Securing the Database of Humanity: Design encryption, access boundaries, retention, and abuse resistance.
• Multi-Tenant Isolation: Ensure boundaries between tenants, roles, and studies hold up.
• AI-Native Attack Surface: Threat-model prompt injection, data exfiltration, tool and agent permissions.
• Securing the Human API: Build authentication, authorization, and API surfaces for programmatic and agentic callers.
• Security Engineering Platform: Build secure-by-default libraries, SAST/DAST/SCA and secrets scanning, dependency and supply chain hygiene.
• Design and Code Review: Review architecture and pull requests alongside engineers.

📌 Required Qualifications

• You're an engineer first, comfortable in a modern backend stack (TypeScript and Terraform).
• You understand how things are built and how they break, thinking in trust boundaries, threat models, and blast radius.
• You build the fix, not just the finding, shipping guardrails, libraries, pipeline checks, or patches.
• You have real depth in application security fundamentals: authentication and authorization (OAuth/OIDC, sessions, RBAC), cloud and infrastructure security basics, secrets management, secure API design, and common vulnerability classes.
• You're curious about AI security, excited to learn how LLM systems fail and to help define best practices.
• You care about getting things right, going to root cause when something breaks.
• You communicate complex ideas in writing, making the case for tradeoffs, explaining risk to engineers, and getting fixes prioritized.
• You solve problems end to end, scoping your own work, thinking about customers and their trust, and owning your decisions.

⭐ Desirable Experience

• Prior LLM security experience.

🎁 Benefits

Health, covered: Full medical, dental, and vision. FSA/HSA and life insurance are available too. Competitive Compensation: The range for this role is $180,000 – $300,000 base. Actual compensation is influenced by a wide array of factors, including but not limited to skill set, experience, and work location. Annual Learning Stipend: Books, courses, conferences.

🛂 Visa & Eligibility

No visa or eligibility information provided.