Senior Application Security Engineer, AI and Machine Learning

Location: Hybrid in Seattle or San Francisco, United States, with at least 2 days per week in the office and occasional offsites

Annual base salary: $180,000–$220,000 USD, plus potential bonus, equity, and benefits.

Company

hirify.global builds an end-to-end platform for developing, training, and deploying AI systems, combining developer-focused software with large-scale AI compute.

What you will do

• Perform threat modeling and architecture security reviews across AI platforms, inference services, ML pipelines, APIs, and distributed systems.
• Identify and mitigate prompt injection, model extraction, adversarial input, data leakage, and abuse risks.
• Partner with ML, platform, and infrastructure engineers to secure training, fine-tuning, deployment, and model-serving workflows.
• Design isolation, rate limiting, authentication, authorization, service-to-service communication, and workload protection controls for multi-tenant AI systems.
• Secure model artifacts, open-source dependencies, container images, runtime environments, and distribution pipelines through integrity and provenance controls.
• Build security automation, monitoring, detection, scanning, and developer guardrails integrated into CI/CD workflows.

Requirements

• Strong application security engineering experience, including threat modeling, architecture reviews, code reviews, and security improvement implementation.
• Experience securing APIs, distributed systems, cloud environments such as AWS, GCP, or Azure, containers, and Kubernetes.
• Strong scripting or programming skills in Python, Go, or a similar language.
• Experience securing ML pipelines, inference systems, or data platforms, including model-serving architecture and training data security.
• Understanding of prompt injection, model extraction, adversarial inputs, and data leakage risks.
• Visa sponsorship is not available for this role.

Nice to have

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

Culture & Benefits

• Fast-moving, ownership-oriented environment focused on open communication, continuous improvement, and scalable systems.
• Medical, dental, and vision coverage, equity, and U.S. 401(k) matching.
• Unlimited PTO, company holidays, floating holidays, and a two-week winter break.
• Paid parental and family leave, wellness and work-from-home stipends, and an annual learning allowance.
• Four weeks of paid sabbatical after four years of service and complimentary office meals.