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Artificial Intelligence, Computer Engineering, or a related field.\nSoftware development: Strong hands-on programming skills, particularly in Python, with experience in Java, Node.js, Go, C/C++, or other modern languages.\nAI and agentic systems: Practical experience with LLMs, AI agents, tool calling, orchestration frameworks, APIs, and agentic AI security harnesses.\nSecurity engineering: Strong knowledge of application security, AI security, vulnerability research, threat modelling, secure development, network security, infrastructure security, and security architecture.\nCloud-native engineering: Experience with cloud platforms, containers, security tools, automation, integrations, and test environments.\nResearch and prototyping: Demonstrated ability to turn research hypotheses into experiments, working code, prototypes, proofs of concept, and measurable cybersecurity capabilities.\nProduct evaluation: Hands-on ability to test and benchmark cybersecurity products or startups, validate vendor claims, and assess security, scalability, integration complexity, and enterprise applicability.\nOperationalization: Ability to help transition successful research prototypes towards operational or enterprise use.\nEmerging technologies: Ability to research AI security, agentic AI, application security, quantum/post-quantum cryptography, blockchain, and other emerging cybersecurity technologies.\nCommunication: Strong technical writing and presentation skills, with the ability to explain findings and recommendations to engineering teams, security leaders, and investment stakeholders.\nKey Responsibilities\nMust-Have Skills\nEducation: Master’s degree in Cybersecurity, Computer Science, Artificial Intelligence, Computer Engineering, or a related field.\nSoftware development: Strong hands-on programming skills, particularly in Python, with experience in Java, Node.js, Go, C/C++, or other modern languages.\nAI and agentic systems: Practical experience with LLMs, AI agents, tool calling, orchestration frameworks, APIs, and agentic AI security harnesses.\nSecurity engineering: Strong knowledge of application security, AI security, vulnerability research, threat modelling, secure development, network security, infrastructure security, and security architecture.\nCloud-native engineering: Experience with cloud platforms, containers, security tools, automation, integrations, and test environments.\nResearch and prototyping: Demonstrated ability to turn research hypotheses into experiments, working code, prototypes, proofs of concept, and measurable cybersecurity capabilities.\nProduct evaluation: Hands-on ability to test and benchmark cybersecurity products or startups, validate vendor claims, and assess security, scalability, integration complexity, and enterprise applicability.\nOperationalization: Ability to help transition successful research prototypes towards operational or enterprise use.\nEmerging technologies: Ability to research AI security, agentic AI, application security, quantum/post-quantum cryptography, blockchain, and other emerging cybersecurity technologies.\nCommunication: Strong technical writing and presentation skills, with the ability to explain findings and recommendations to engineering teams, security leaders, and investment stakeholders.\nSkill Requirements\nSecurity Engineer / Technical Security Research Engineer\nMust-Have and Nice-to-Have Skills\nMust-Have Skills\nEducation: Master’s degree in Cybersecurity, Computer Science, Artificial Intelligence, Computer Engineering, or a related field.\nSoftware development: Strong hands-on programming skills, particularly in Python, with experience in Java, Node.js, Go, C/C++, or other modern languages.\nAI and agentic systems: Practical experience with LLMs, AI agents, tool calling, orchestration frameworks, APIs, and agentic AI security harnesses.\nSecurity engineering: Strong knowledge of application security, AI security, vulnerability research, threat modelling, secure development, network security, infrastructure security, and security architecture.\nCloud-native engineering: Experience with cloud platforms, containers, security tools, automation, integrations, and test environments.\nResearch and prototyping: Demonstrated ability to turn research hypotheses into experiments, working code, prototypes, proofs of concept, and measurable cybersecurity capabilities.\nProduct evaluation: Hands-on ability to test and benchmark cybersecurity products or startups, validate vendor claims, and assess security, scalability, integration complexity, and enterprise applicability.\nOperationalization: Ability to help transition successful research prototypes towards operational or enterprise use.\nEmerging technologies: Ability to research AI security, agentic AI, application security, quantum/post-quantum cryptography, blockchain, and other emerging cybersecurity technologies.\nCommunication: Strong technical writing and presentation skills, with the ability to explain findings and recommendations to engineering teams, security leaders, and investment stakeholders.\nNice-to-Have Skills\nAdvanced education: PhD in Cybersecurity, Computer Science, Artificial Intelligence, Computer Engineering, or a related field.\nAI offensive security: Experience with AI red teaming, autonomous penetration testing, agent security, or AI-native security tooling.\nResearch recognition: Research papers or presentations at recognized cybersecurity, AI, or systems forums.\nInnovation evidence: Patents, open-source security projects, vulnerability research, or other demonstrated technical innovation.\nStartup experience: Cybersecurity startup, founder, or early-stage product experience.\nInvestment engagement: Experience pitching to venture capital firms, corporate venture teams, accelerators, or other investment stakeholders.\nCertifications: CISSP, OSCP, CSSLP, or equivalent cybersecurity certification.\nHybrid mindset: Ability to combine the perspectives of a security researcher, software engineer, and emerging-technology evaluator.\nOther Requirements\nAdvanced education: PhD in Cybersecurity, Computer Science, Artificial Intelligence, Computer Engineering, or a related field.\nAI offensive security: Experience with AI red teaming, autonomous penetration testing, agent security, or AI-native security tooling.\nResearch recognition: Research papers or presentations at recognized cybersecurity, AI, or systems forums.\nInnovation evidence: Patents, open-source security projects, vulnerability research, or other demonstrated technical innovation.\nStartup experience: Cybersecurity startup, founder, or early-stage product experience.\nInvestment engagement: Experience pitching to venture capital firms, corporate venture teams, accelerators, or other investment stakeholders.\nCertifications: CISSP, OSCP, CSSLP, or equivalent cybersecurity certification.\n Hybrid mindset: Ability to combine the perspectives of a security researcher, software engineer, and emerging-technology evaluator.\nAI; Python; Java; Node / Node JS; Go; Cryptography; Threat Vulnerability; Firewall; API; Docker; Git (GitHub, GitLab, BitBucket, SVN); Gradle; JFrog; Kubernetes; Linux; Maven; Palo Alto","description_format":"text","description_chars":7264,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"master","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Smart Contracts & Security","Information Security","IT Consulting & Digital Transformation","Systems Integrators"],"lifecycle":[{"event":"open","at":"2026-10-18T09:41:23Z"}],"visa":[],"liveness":{"score":86,"band":"hot","label":"Hiring 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