Diopter is an AI deepfake and social research cybersecurity platform being created to help defend companies against AI social engineering attacks. With experienced generative AI founders Rohan Gupta (prev. CEO and Co-Founder of QuillBot, 35M+ monthly active users and $200M exit) and Jeremy Pippin (VP Product at QuillBot & FanDuel), Diopter is focused on offering world-class deepfake detection and social engineering production to SMB and mid-market companies across the United States and Canada. Key Responsibilities: Design and build detection pipelines for synthetic video and audio, including integration of AI/ML models for deepfake identification Research and implement techniques for conversation arc analysis: detecting manipulation patterns such as authority spoofing, urgency injection, and social isolation across multi-turn interactions Build identity verification layers that work in real-time video and audio contexts Develop adversarial testing frameworks to stress-test our detection models against evolving attack techniques (voice cloning, face-swapping, real-time deepfakes) Contribute to the architecture of our desktop-native detection agent, ensuring low-latency analysis without compromising accuracy Stay current on the threat landscape: new generative AI capabilities, emerging social engineering vectors, and novel attack surfaces Internal Security & Infrastructure Design and implement endpoint security controls across company devices (macOS/Linux), including disk encryption, device management, and access policies Build and maintain DLP policies to protect sensitive data (customer data, model weights, proprietary detection logic) Configure and manage cloud security controls across our infrastructure (AWS/GCP), including IAM, network segmentation, logging, and secrets management Implement monitoring and alerting for security-relevant events across infrastructure and application layers Develop and maintain security baselines, hardening guides, and compliance documentation as we pursue enterprise customer requirements Automation & Operations Automate security workflows: deployment hardening, configuration audits, vulnerability scanning, and agent health checks using Python, Bash, or infrastructure-as-code tools Maintain documentation including architecture diagrams, deployment procedures, and incident response playbooks Support security reviews for new features and integrations Requirements: Strong understanding of how social engineering attacks work in practice, from phishing and vishing to deepfake-enabled impersonation Hands-on experience with at least some of: audio/video processing pipelines, ML model deployment, or real-time streaming analysis Solid knowledge of endpoint and cloud security fundamentals: encryption, access control, network segmentation, logging Experience securing cloud infrastructure (AWS or GCP preferred) Proficiency in Python; Bash and familiarity with CI/CD pipelines a plus Understanding of adversarial ML concepts: how generative models can be attacked, evaded, or poisoned Comfort working in a fast-moving startup where you'll wear multiple hats Nice-to-Have: Experience with deepfake detection, synthetic media analysis, or computer vision / audio ML models Familiarity with EDR/NDR platforms (CrowdStrike, Defender, Corelight, etc.) Background in red teaming or penetration testing, particularly social engineering assessments Cloud security certifications (AWS Security Specialty, GCP Professional Cloud Security Engineer) or general certs (CISSP, OSCP, Security+) Experience building security tooling or detection systems from scratch rather than just configuring vendor products