Senior Director, AI Security Systems
New
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JobgetherAI cybersecurity
Full-time remote opportunity based in the United States.Full-TimeDirector
SalaryAnnual base salary ranging from $235,000 to $355,000, depending on experience, qualifications, and location.
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Job Details
- Experience
- 15+ years of progressive professional experience in software engineering, machine learning, or security engineering, including at least 8 years managing engineering or applied research teams and 4 years leading managers across multiple teams.
- Required Skills
- CybersecurityLLMDistributed Systems
Requirements
- Bachelor's, Master's, or PhD in Computer Science, Computer Engineering, Electrical Engineering, Applied Mathematics, or a related technical discipline; an advanced degree is preferred.
- 15+ years of progressive experience in software engineering, machine learning, or security engineering.
- At least 8 years managing engineering or applied research teams and 4 years leading managers across multiple teams.
- Experience architecting, building, and operating production-grade AI or machine-learning security systems in endpoint environments or at large cloud scale.
- Strong understanding of large language models, autonomous and agentic architectures, planning, tool usage, memory management, and context optimization.
- Familiarity with supervised fine-tuning (SFT), RLHF/RLAIF, DPO, GRPO, model evaluation, and inference optimization.
- Cybersecurity expertise in areas such as threat detection and response, threat hunting, malware analysis, vulnerability research, MITRE ATT&CK, or security automation.
- Experience leading teams responsible for distributed systems, high-throughput data infrastructure, real-time analytics, and GPU-based inference platforms.
- Track record of building and scaling technical teams, developing leaders, managing performance, and maintaining engineering standards.
- Ability to communicate complex technical concepts as strategic recommendations and align stakeholders across departments.
- Additional experience in cybersecurity leadership, frontier AI research, adversarial machine learning, AI red teaming, or autonomous cybersecurity systems is preferred.
- Research publications, patents, influential open-source projects, or presentations at leading AI and cybersecurity conferences are considered a plus.
Responsibilities
- Build, lead, and scale an organization of engineering managers, principal engineers, and research scientists.
- Define and execute the engineering strategy and roadmap for AI security systems, including objectives, performance indicators, and investment priorities.
- Lead development and deployment of AI-powered endpoint security capabilities under latency, memory, and computing constraints.
- Oversee cloud-scale AI infrastructure, including distributed detection pipelines, real-time inference platforms, model routing, and GPU-efficient serving.
- Move autonomous AI agents into production for security investigation, threat hunting, detection engineering, incident response, and remediation.
- Establish processes for translating AI research into reliable, scalable products through research and engineering collaboration.
- Define evaluation frameworks, benchmarks, and testing environments for detection accuracy, reliability, false positives, latency, and cost.
- Ensure AI systems resist adversarial manipulation, data poisoning, prompt injection, evasion, and misuse of automated tools.
- Align technical initiatives with product, engineering, threat intelligence, security operations, and executive stakeholders.
- Communicate priorities, technical decisions, progress, risks, and investment opportunities to senior executives and stakeholders.
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