Senior Application Security Engineer, AI and Machine Learning

What you'll do

• Threat-model AI platforms and ML pipelines; review inference architectures and secure training, fine-tuning, and deployment workflows.
• Review application architectures and high-risk code; help engineers implement secure APIs, distributed systems, and security guardrails.
• Build security automation, monitoring, and controls for inference services, model supply chains, and multi-tenant workloads.

What they ask for

• Strong background in application security engineering, including threat modeling and architecture reviews.
• Experience securing APIs and distributed systems in cloud environments such as AWS, GCP, or Azure.
• Experience with containers and Kubernetes, plus strong scripting or programming skills such as Python or Go.
• Experience securing ML pipelines, inference systems, or data platforms; familiarity with AI risks and model-serving architecture reviews.

Nice to have

• Red team or offensive security experience, GPU infrastructure or high-performance computing, or multi-tenant infrastructure security.
• Experience with Hugging Face, PyTorch, TensorFlow, LLM systems, RAG pipelines, agent frameworks, or security automation pipelines.

Pay

$180,000 — $220,000 USD annual base salary

Tools

AWS, GCP, Azure, Kubernetes, Python, Go, Hugging Face, PyTorch

AI focus

Secures AI/ML platforms, inference systems, model pipelines, and AI supply chains; addresses risks including prompt injection, model extraction, adversarial inputs, and data leakage.