AI Lead (Small Language Models + Cybersecurity)
Location:
San Francisco Bay Area (preferred) / Remote
Company:
Protocol Nine About the Role We are looking for an AI Lead to build the core intelligence layer of an AI-native security platform. This role sits at the intersection of small language model (SLM) development, agentic systems, and cybersecurity , and will define how models reason about intent, risk, and behavior in real-world environments. You will lead the design, training, and deployment of specialized models that operate in constrained, high-performance environments (e.g., edge, real-time inference), and apply them to security problems such as threat detection, policy enforcement, and autonomous decision-making. What You’ll Do Design & Train Small Language Models (SLMs) Build domain-specific models optimized for latency, cost, and controllability Fine-tune models on security datasets (logs, network traffic, code, policies) Develop techniques for distillation, quantization, and efficient inference Build AI-Native Security Systems Architect models that reason about intent in security contexts
Develop detection systems for threats across:
Network traffic Application behavior Integrate models into real-time decision pipelines (e.g., firewall, policy engine) Agentic AI & Decision Systems Design multi-agent systems for continuous monitoring, analysis, and response Implement feedback loops between detection, reasoning, and enforcement layers Ensure reliability, explainability, and controllability of autonomous systems Model Infrastructure & Deployment Optimize models for edge + distributed environments Build evaluation frameworks for adversarial robustness and false positives Work closely with engineering to productionize models (APIs, pipelines, scaling) Security Research & Innovation Stay ahead of emerging threats (e.g., AI-generated attacks, supply chain risks) Experiment with novel approaches (e.g., semantic code analysis, intent verification) Contribute to technical strategy and product direction What We’re Looking For Core Requirements 5+ years in machine learning / AI engineering (or equivalent depth) Hands-on experience training or fine-tuning small or specialized language models
Strong understanding of:
Transformer architectures Model optimization (quantization, pruning, distillation) Evaluation and benchmarking Cybersecurity Experience
Experience in at least one area:
Network security / firewalls Endpoint or cloud security Application security or code analysis
Familiarity with:
Threat detection systems Logs, telemetry, and security data pipelines Adversarial attack vectors Systems & Engineering Strong programming skills (Python + ML frameworks like PyTorch/JAX) Experience deploying models in production environments Understanding of distributed systems and real-time inference constraints Nice to Have Experience with edge AI or low-latency systems Familiarity with agent frameworks / multi-agent systems Contributions to open-source ML or security projects
Compensation
Competitive salary + equity Early-stage ownership and high impact Opportunity to define a new category in security