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Lightning AILightning AISan Francisco, CA

Senior Application Security Engineer, AI and Machine Learning

Secures AI/ML systems through threat modeling, architecture reviews, and securing inference pipelines, APIs, and model supply chains. Partners with ML engineers to embed security in training, deployment, and multi-tenant workloads while building automation tooling.

180k – 220k/yr
HybridSecurity Engineering

About the role

What You’ll Do

Secure AI and Machine Learning Systems

  • Perform threat modeling across AI platforms, inference services, and ML pipelines
  • Identify risks such as prompt injection, model extraction, adversarial inputs, and data leakage
  • Review model serving architectures and inference pipelines
  • Partner with ML engineers to secure training, fine tuning, and deployment workflows
  • Help design isolation and security controls for multi tenant AI workloads

Application Security Engineering

  • Perform architecture and design security reviews
  • Conduct targeted code reviews for high risk components
  • Identify security gaps in APIs, micro-services, and distributed systems
  • Build secure patterns for authentication, authorization, and service to service communication
  • Help engineering teams implement secure defaults and guardrails

Inference Platform Security

  • Secure customer facing inference APIs and services
  • Protect against abuse, model extraction, and adversarial behavior
  • Design rate limiting, isolation, and workload protection controls
  • Build monitoring and detection for anomalous inference behavior

AI Supply Chain and Model Security

  • Evaluate open source models and dependencies
  • Secure model artifacts and distribution pipelines
  • Implement integrity validation and provenance controls
  • Help secure container images and runtime environments

Security Automation and Tooling

  • Build security automation for AI and application pipelines
  • Integrate security scanning into CI/CD workflows
  • Develop tooling to help engineers detect and fix issues early
  • Improve developer experience with security guardrails

What You'll Need

Required Experience

  • Strong background in application security engineering
  • Experience performing threat modeling and architecture reviews
  • Experience securing APIs and distributed systems
  • Experience working in cloud environments such as AWS, GCP, or Azure
  • Experience with containers and Kubernetes
  • Strong scripting or programming skills such as Python, Go, or similar
  • Experience working closely with engineering teams to implement security improvements

AI and Machine Learning Experience

  • Experience securing ML pipelines, inference systems, or data platforms
  • Familiarity with risks such as prompt injection, model extraction, and adversarial inputs
  • Experience reviewing model serving architectures
  • Understanding of training data security and data leakage risks

It's a Strong Plus If You Have

  • Red team or offensive security experience
  • Experience crafting payloads and evaluating CVEs for exploitability in diverse environments
  • Experience with GPU infrastructure or high performance computing
  • Experience with Hugging Face, PyTorch, TensorFlow, or similar frameworks
  • Experience with LLM systems, RAG pipelines, or agent frameworks
  • Experience building security automation pipelines
  • Experience securing multi tenant infrastructure

Skills

KubernetesAWSGCPAzurePythonGoPyTorchTensorFlowHugging FaceCI/CD
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