{"schemaVersion":"jobsearcher.job.v1","id":"3eaa433b3f2b5d5fb4cb1565","url":"https://jobsearcher.com/jobs/3eaa433b3f2b5d5fb4cb1565","canonicalUrl":"https://jobsearcher.com/jobs/3eaa433b3f2b5d5fb4cb1565","title":"Lead Engineer (Breach & Attack Simulation)","description":"Experience: Senior Level\nSalary: $250,000 - $400,000 per year\n\nJob Details\n-\n\nWhat You'll Build\n\nYou'll take substantial technical ownership of an AI Attack Simulation platform designed to help customers identify vulnerabilities across AI models, applications, LLM-powered systems, and emerging agentic workflows.\n\nThis isn't a traditional penetration-testing position, and it isn't simply another LLM application development role.\n\nYou'll be responsible for helping productize offensive security techniques—turning attacks, adversarial behaviors, and security-testing methodologies into scalable software that customers can continuously use to understand and improve the security posture of their AI environments.\n\nDepending on your background, that could include areas such as:\n\nAI red teaming and automated attack simulation\nAdversary emulation and breach & attack simulation\nAdversarial machine learning\nLLM and AI application security testing\nPrompt injection, jailbreaks, model manipulation, and emerging AI attack techniques\nAutonomous or agentic offensive-security workflows\nContinuous security validation\nAutomated penetration-testing concepts\nAttack orchestration and execution\nDetection, measurement, and analysis of attack outcomes\nWhat Makes This Role Different\n\nEngineering is intentionally being pushed much closer to the customer and the actual problem being solved.\n\nYou'll work within a small, autonomous engineering pod, partnering closely with the individual responsible for stewarding the product. Engineers aren't expected to simply receive requirements from Product and disappear into a backlog.\n\nYou'll help:\n\nSpeak directly with customers and understand their security problems\nDetermine what should actually be built\nPrototype and validate ideas quickly\nMake architectural and technical decisions without excessive bureaucracy\nBuild production-quality systems\nAnalyze product and customer-usage data\nValidate solutions with customers\nIterate rapidly based on what you learn\n\nThe company wants engineers who are comfortable operating with speed, ambiguity, autonomy, and accountability.\n\nYou won't always have perfect information. The strongest engineers here are able to absorb context, make a thoughtful decision, execute, learn, and adjust rather than waiting for every variable to be resolved.\n\nThe Technical Environment\n\nThe broader engineering environment includes technologies such as:\n\nGo | Python | Redis | OpenSearch | Kubernetes | AWS | Microservices | AI/LLM Systems | Agentic AI\n\nExact language alignment is less important than engineering depth.\n\nIf you've spent your career building sophisticated systems in another modern language but have deep offensive-security knowledge and can quickly become productive in Go/Python environments, we still want to talk.\n\nThe Profile We're Looking For\n\nThe ideal candidate sits somewhere at the intersection of:\n\nOffensive Security × Production Software Engineering × AI/ML Security × Agentic Systems × Product Engineering\n\nYou may currently be a:\n\nStaff Software Engineer\nPrincipal Software Engineer\nLead Engineer\nSecurity Research Engineer\nOffensive Security Engineer\nAI Security Engineer\nAdversarial ML Engineer\nRed Team Engineer\nSecurity Product Engineer\nFounding Engineer\n\nWe're especially interested in engineers who have built products involving AI red teaming, breach & attack simulation, adversary emulation, automated penetration testing, continuous security validation, autonomous security agents, or AI/ML security.\n\nWhat We're NOT Looking For\n\nThis distinction is important.\n\nWe're not searching for a traditional penetration tester whose experience stops at identifying vulnerabilities and writing reports.\n\nWe're also not searching for an AI researcher whose primary output has been papers, experiments, or notebooks.\n\nAnd simply building an LLM-powered application isn't enough.\n\nWe need someone who understands how sophisticated attacks work and has the software engineering ability to turn those concepts into reliable, scalable, production-grade technology.\n\nYou need to be a builder.\n\nYou'll Likely Thrive Here If You...\nNaturally think about systems from an attacker's perspective\nHave deep production software engineering experience\nHave worked with offensive-security, adversary-emulation, attack-simulation, or AI-security concepts\nAre actively experimenting with or building agentic/LLM systems\nCan move comfortably between architecture and hands-on implementation\nEnjoy owning ambiguous technical problems rather than waiting for detailed specifications\nCan make sound technical decisions quickly\nWant direct exposure to customers and product strategy\nPrefer small, high-output engineering teams over layers of process\nCan operate effectively in a rapidly evolving startup environment\n\nA bit about us:\n-\n\nWe are partnering with a rapidly growing, well-funded AI cybersecurity company that is building technology designed to protect the AI systems, applications, models, and autonomous agents increasingly being deployed across the enterprise and government.\n\nFollowing a major new round of funding, the company is expanding its approximately 30-person engineering organization and rethinking how products are built. Rather than large teams executing against predefined tickets, engineering is moving toward small, highly empowered three-person pods that own problems from customer discovery through architecture, development, validation, and production delivery.\n\nWe are searching for an exceptional Lead Engineer for the company's AI Attack Simulation platform.\n\nDon't let the \"Lead\" title undersell the opportunity. This is essentially a Staff/Principal-level hands-on engineering role for someone who can combine deep software engineering ability with an attacker's mindset.\n\nThe central question behind the product is simple:\n\nHow would an attacker compromise this AI system—and how can we safely, repeatedly, and measurably reproduce those attacks before a real adversary does?\n\nYou'll help answer that question in production.\n\nWhy join us?\n-\n\nThe company operates at the convergence of two of the most consequential technology categories today: artificial intelligence and cybersecurity.\n\nIts broader platform helps organizations discover and understand the AI systems operating throughout their environments, protect AI applications at runtime, secure LLM/chatbot and agent workflows, simulate attacks against AI systems, monitor emerging coding-agent activity, and understand compliance with organizational and government security requirements.\n\nFollowing a significant new funding round, the company is entering its next stage of growth while intentionally keeping engineering teams small and highly empowered.\n\nThis is an opportunity to join while many of the architectural, product, and engineering decisions are still being made—and have meaningful influence over them.\n\nCompensation: $250K–$350K base salary + meaningful equity\n\nLocation: Fully Remote – U.S\n\n#techservices #python #go #distributed-systems #ai-security #adversary-emulation #ai-red-team #breach-and-attack-simulation #automated-penetration-testing #tier3","company":"Leoforce","rawCompany":"leoforce","city":"Los Angeles","state":"CA","isRemote":false,"isActive":false,"createdAt":"2026-09-02T10:43:27.047Z","occupations":[{"code":"15-1299.05","title":"Information Security Engineers","slug":"information-security-engineers"},{"code":"15-1299.04","title":"Penetration Testers","slug":"penetration-testers"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Lead Engineer (Breach & Attack Simulation)","description":"Experience: Senior Level\nSalary: $250,000 - $400,000 per year\n\nJob Details\n-\n\nWhat You'll Build\n\nYou'll take substantial technical ownership of an AI Attack Simulation platform designed to help customers identify vulnerabilities across AI models, applications, LLM-powered systems, and emerging agentic workflows.\n\nThis isn't a traditional penetration-testing position, and it isn't simply another LLM application development role.\n\nYou'll be responsible for helping productize offensive security techniques—turning attacks, adversarial behaviors, and security-testing methodologies into scalable software that customers can continuously use to understand and improve the security posture of their AI environments.\n\nDepending on your background, that could include areas such as:\n\nAI red teaming and automated attack simulation\nAdversary emulation and breach & attack simulation\nAdversarial machine learning\nLLM and AI application security testing\nPrompt injection, jailbreaks, model manipulation, and emerging AI attack techniques\nAutonomous or agentic offensive-security workflows\nContinuous security validation\nAutomated penetration-testing concepts\nAttack orchestration and execution\nDetection, measurement, and analysis of attack outcomes\nWhat Makes This Role Different\n\nEngineering is intentionally being pushed much closer to the customer and the actual problem being solved.\n\nYou'll work within a small, autonomous engineering pod, partnering closely with the individual responsible for stewarding the product. Engineers aren't expected to simply receive requirements from Product and disappear into a backlog.\n\nYou'll help:\n\nSpeak directly with customers and understand their security problems\nDetermine what should actually be built\nPrototype and validate ideas quickly\nMake architectural and technical decisions without excessive bureaucracy\nBuild production-quality systems\nAnalyze product and customer-usage data\nValidate solutions with customers\nIterate rapidly based on what you learn\n\nThe company wants engineers who are comfortable operating with speed, ambiguity, autonomy, and accountability.\n\nYou won't always have perfect information. The strongest engineers here are able to absorb context, make a thoughtful decision, execute, learn, and adjust rather than waiting for every variable to be resolved.\n\nThe Technical Environment\n\nThe broader engineering environment includes technologies such as:\n\nGo | Python | Redis | OpenSearch | Kubernetes | AWS | Microservices | AI/LLM Systems | Agentic AI\n\nExact language alignment is less important than engineering depth.\n\nIf you've spent your career building sophisticated systems in another modern language but have deep offensive-security knowledge and can quickly become productive in Go/Python environments, we still want to talk.\n\nThe Profile We're Looking For\n\nThe ideal candidate sits somewhere at the intersection of:\n\nOffensive Security × Production Software Engineering × AI/ML Security × Agentic Systems × Product Engineering\n\nYou may currently be a:\n\nStaff Software Engineer\nPrincipal Software Engineer\nLead Engineer\nSecurity Research Engineer\nOffensive Security Engineer\nAI Security Engineer\nAdversarial ML Engineer\nRed Team Engineer\nSecurity Product Engineer\nFounding Engineer\n\nWe're especially interested in engineers who have built products involving AI red teaming, breach & attack simulation, adversary emulation, automated penetration testing, continuous security validation, autonomous security agents, or AI/ML security.\n\nWhat We're NOT Looking For\n\nThis distinction is important.\n\nWe're not searching for a traditional penetration tester whose experience stops at identifying vulnerabilities and writing reports.\n\nWe're also not searching for an AI researcher whose primary output has been papers, experiments, or notebooks.\n\nAnd simply building an LLM-powered application isn't enough.\n\nWe need someone who understands how sophisticated attacks work and has the software engineering ability to turn those concepts into reliable, scalable, production-grade technology.\n\nYou need to be a builder.\n\nYou'll Likely Thrive Here If You...\nNaturally think about systems from an attacker's perspective\nHave deep production software engineering experience\nHave worked with offensive-security, adversary-emulation, attack-simulation, or AI-security concepts\nAre actively experimenting with or building agentic/LLM systems\nCan move comfortably between architecture and hands-on implementation\nEnjoy owning ambiguous technical problems rather than waiting for detailed specifications\nCan make sound technical decisions quickly\nWant direct exposure to customers and product strategy\nPrefer small, high-output engineering teams over layers of process\nCan operate effectively in a rapidly evolving startup environment\n\nA bit about us:\n-\n\nWe are partnering with a rapidly growing, well-funded AI cybersecurity company that is building technology designed to protect the AI systems, applications, models, and autonomous agents increasingly being deployed across the enterprise and government.\n\nFollowing a major new round of funding, the company is expanding its approximately 30-person engineering organization and rethinking how products are built. Rather than large teams executing against predefined tickets, engineering is moving toward small, highly empowered three-person pods that own problems from customer discovery through architecture, development, validation, and production delivery.\n\nWe are searching for an exceptional Lead Engineer for the company's AI Attack Simulation platform.\n\nDon't let the \"Lead\" title undersell the opportunity. This is essentially a Staff/Principal-level hands-on engineering role for someone who can combine deep software engineering ability with an attacker's mindset.\n\nThe central question behind the product is simple:\n\nHow would an attacker compromise this AI system—and how can we safely, repeatedly, and measurably reproduce those attacks before a real adversary does?\n\nYou'll help answer that question in production.\n\nWhy join us?\n-\n\nThe company operates at the convergence of two of the most consequential technology categories today: artificial intelligence and cybersecurity.\n\nIts broader platform helps organizations discover and understand the AI systems operating throughout their environments, protect AI applications at runtime, secure LLM/chatbot and agent workflows, simulate attacks against AI systems, monitor emerging coding-agent activity, and understand compliance with organizational and government security requirements.\n\nFollowing a significant new funding round, the company is entering its next stage of growth while intentionally keeping engineering teams small and highly empowered.\n\nThis is an opportunity to join while many of the architectural, product, and engineering decisions are still being made—and have meaningful influence over them.\n\nCompensation: $250K–$350K base salary + meaningful equity\n\nLocation: Fully Remote – U.S\n\n#techservices #python #go #distributed-systems #ai-security #adversary-emulation #ai-red-team #breach-and-attack-simulation #automated-penetration-testing #tier3","datePosted":"2026-09-02T10:43:27.047Z","dateModified":"2026-09-02T10:43:27.047Z","hiringOrganization":{"@type":"Organization","name":"Leoforce","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Los Angeles","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"3eaa433b3f2b5d5fb4cb1565"},"url":"https://jobsearcher.com/jobs/3eaa433b3f2b5d5fb4cb1565"}}