Senior Application Security Engineer, AI and Machine Learning

Lightning AI•Seattle, WA

3d•$180,000 - $220,000•Hybrid

About The Position

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. We are looking for a Senior Application Security Engineer to help secure our AI, machine learning, and inference platforms. This is a hands on technical role focused on building security into modern AI infrastructure, inference systems, and developer platforms. You will work closely with platform engineers, ML engineers, and infrastructure teams to identify risks, design secure architectures, and build security tooling that enables engineers to move quickly and safely. This role is execution focused. You will drive technical implementation, perform deep security reviews, and help build out our application security capabilities alongside the CISO and engineering leadership. This is a hybrid role based in either our Seattle or San Francisco office. The anticipated salary range for this role is $180,000 - $220,000.

Requirements

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 Haves

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

Responsibilities

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

Benefits

We offer competitive base salaries and equity with a 25% one year cliff and monthly vesting thereafter.
For our international employees, we work with our EOR to pay you in your local currency and provide equitable benefits across the globe.
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