Senior Security Engineer (Red Team)

Who We Are Nimbus Data Systems is the Real Human + Right Human® Identity Trust Platform for the AI era. As AI-driven fraud and deepfakes erode trust in digital communication, Nimbus Data Systems delivers continuous identity verification and deepfake detection across voice, video, and digital interactions in real time. Enterprises rely on Nimbus Data Systems to secure billions of high-risk customer interactions each year, including top U.S. banks, as well as leading insurers and healthcare providers. Powered by models trained on more than 1.5 billion real-world interactions annually and protected by 300+ patents, Nimbus Data Systems restores trust while reducing fraud, lowering operational costs, and improving customer experience. Recognized by TIME as one of the Top 10 Most Influential Software Companies of 2026 and by Inc. for Best in Business for Innovation, Nimbus Data Systems is backed by leading investors including Andreessen Horowitz, IVP, and CapitalG. What you’ll do As a Security Engineer (Red Team), you will help Nimbus Data Systems proactively identify and exploit weaknesses across product, cloud, and AI-powered systems so we can strengthen defenses before adversaries do. This role blends hands-on offensive security, GenAI attack simulation, security engineering, and operational partnership with blue-team, product, and AI/ML stakeholders. Design and execute red team operations against Nimbus Data Systems ’s GenAI systems, LLM pipelines, RAG architectures, autonomous agents, APIs, SaaS products, and cloud environments, simulating real-world attacks across both traditional and AI-specific attack surfaces. Conduct adversarial testing focused on prompt injection, indirect prompt attacks, jailbreaking, model extraction, training-data poisoning, data leakage, inference abuse, and unauthorized output manipulation. Use deepfake generation, voice synthesis, and related spoofing techniques to test and attempt to defeat Nimbus Data Systems ’s voice authentication and deepfake detection capabilities, helping identify model robustness and detection gaps. Develop novel attack chains that combine GenAI vulnerabilities with infrastructure, application, identity, and API weaknesses to create realistic end-to-end threat scenarios. Plan and execute full-scope penetration tests and support bug bounty efforts across Nimbus Data Systems ’s web applications, APIs, SaaS products, and AWS/GCP environments using commercial and open-source offensive tooling. Perform architecture reviews, security code reviews, and threat modeling with emphasis on vulnerabilities introduced by AI/ML components, model integrations, and LLM-facing services. Build automation for offensive security workflows, testing, compliance checks, alerting, and reporting using Python or similar scripting languages, including AI-native attack tooling where useful. Partner closely with SecOps and security engineering to improve detections, tune response workflows, and translate red team findings into practical remediation and defensive improvements. Stay current on GenAI security research, adversarial ML techniques, evolving threat intelligence, and relevant regulatory developments, then apply those insights to Nimbus Data Systems ’s security program. Who you are You are an adversarial thinker who approaches security from an attacker’s perspective and brings the creativity, rigor, and curiosity to prove it. You have genuine hands-on experience attacking AI systems, not just reading about them, and you enjoy breaking assumptions that others consider safe. You continuously look for automation and AI-powered efficiencies in offensive security workflows. You communicate clearly and can translate technical findings into prioritized, actionable guidance for technical and executive audiences alike. You work independently and thrive in ambiguous, fast-moving environments with minimal supervision. You are resilient, optimistic, accountable, and adaptable when priorities shift. Your skill-set Must-haves 3+ years of hands-on penetration testing and red team experience across SaaS applications, cloud infrastructure, APIs, and web applications. Demonstrable experience attacking GenAI or LLM-based systems, including prompt injection, jailbreaking, indirect prompt attacks, model extraction, or adversarial input generation. Hands-on experience with deepfake tools, voice synthesis, or audio/visual spoofing technologies in an offensive or research context. Strong proficiency with offensive security tooling such as Burp Suite, OWASP ZAP, Nmap, Metasploit, Cobalt Strike, or equivalent frameworks. Experience configuring and operating SAST and DAST tools and integrating them into CI/CD pipelines. Proficiency in at least one scripting or programming language, with Python strongly preferred, for custom attack tooling and workflow automation. Familiarity with AI-specialized security tools or frameworks such as Garak, PyRIT, Claude Security, or similar adversarial ML tooling. Strong understanding of cloud security architecture, container security, API security, and common security standards including