AI Lead

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