$180,000 – $220,000/yr

Senior Application Security Engineer, AI and Machine Learning

United StatesSan Francisco · Seattlesenior
EngineeringData ScienceSecurityOtherSecurity Engineer
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Quick Summary

Overview

Who We Are Lightning AI is the company behind PyTorch Lightning. Founded in 2019, we build an end-to-end platform for developing, training,

Technical Tools
EngineeringData ScienceSecurityOtherSecurity Engineer

Lightning AI is the company behind PyTorch Lightning. Founded in 2019, we build an end-to-end platform for developing, training, and deploying AI systems—designed to take ideas from research to production with less friction.

Through our merger with Voltage Park, a neocloud and AI Factory, Lightning AI combines developer-first software with cost-efficient, large-scale compute. Teams get the tools they need for experimentation, training, and production inference, with security, observability, and control built in.

We serve solo researchers, startups, and large enterprises. Lightning AI operates globally with offices in New York City, San Francisco, Seattle, and London, and is backed by Coatue, Index Ventures, Bain Capital Ventures, and Firstminute.

Responsibilities

~1 min read
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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

Nice to Have

~1 min read
  • 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
  • Security is embedded into AI platform architecture early
  • Engineering teams ship quickly with secure defaults
  • Inference platforms are resilient against abuse and extraction
  • Model pipelines are secure and auditable
  • Security tooling scales with engineering growth

This role sits at the intersection of application security, AI infrastructure, and developer platforms. You will help define how we secure modern AI systems while enabling engineers to move quickly and safely.

You will work closely with engineering leadership and the CISO to build practical, scalable security capabilities that support rapid innovation in AI and machine learning.

What We Offer

~1 min read
Medical, dental and vision
Life and AD&D insurance
Flexible paid time off including winter closure
Paid family leave benefits
$500 one time home office stipend
$1,000 annual learning & development stipend
100% Citibike membership (NYC only)
$45/month gym membership
Additional various medical and mental health services

Listing Details

First seen
April 2, 2026
Last seen
April 26, 2026

Posting Health

Days active
23
Repost count
0
Trust Level
42%
Scored at
April 26, 2026

Signal breakdown

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Senior Application Security Engineer, AI and Machine Learning$180k–$220k