AI Security Engineer

interrahealth; United States; Remote; USD 140,000 - 180,000; Full time

Benefits offered by this job

Remote-first in the US

Home office stipend

Monthly Wi‑Fi reimbursement

Flexible scheduling

Core collaboration hours

23 company holidays

Job summary

InterraHealth is seeking a hands-on security engineer to protect AI/ML components across a healthcare technology platform that helps providers and patients navigate the prescription journey.

You will partner with data and engineering teams to assess models, data pipelines, and AI-enabled applications for vulnerabilities, then build guardrails, monitoring, and incident response for AI‑related security events.

Qualifications

• Bachelor's degree and 5+ years in security engineering or application security, including hands-on experience securing AI/ML systems or LLM-based applications.
• Deep knowledge of AI/ML security risks such as OWASP Top 10 for LLMs, adversarial ML, and data poisoning.
• Experience with SAST/DAST, vulnerability scanning, and scripting in Python or a comparable language.
• Understanding of cloud infrastructure (AWS/Azure/GCP) and how AI/ML workloads are deployed and secured within it.
• Clear communication skills and comfort in a fast-paced environment.

Responsibilities

• Lead security assessments of AI/ML models, data pipelines, and AI-enabled applications, identifying risks such as prompt injection, model inversion, data poisoning, and adversarial inputs.
• Partner with data and engineering teams to embed threat modeling and security requirements into the AI development lifecycle, from data collection through deployment.
• Build and maintain guardrails, monitoring, and detection controls for production AI systems, flagging anomalous model behavior and unauthorized data access.
• Review third-party AI tools, APIs, and vendors, including LLM providers, before integration, and lead incident response for AI-related security events.
• Advise on standards for secure and responsible AI use, validate access controls, encryption, and data segmentation, and use AI tools to accelerate security testing while modeling responsible use.

Skills

Security engineering

Application security

Python scripting

Cloud security

Threat modeling

Education

Bachelor's degree in CS or related field

Tools

SAST/DAST tooling

Job description

Role overview

A hands‑on technical role securing AI and machine learning systems across a healthcare technology platform that helps providers and patients navigate the prescription journey. The engineer partners with data and engineering teams to assess models, data pipelines, and AI-enabled applications for vulnerabilities, then builds the guardrails and monitoring needed to keep them safe in production.

Responsibilities

• Lead security assessments of AI/ML models, data pipelines, and AI-enabled applications, identifying risks such as prompt injection, model inversion, data poisoning, and adversarial inputs
• Partner with data and engineering teams to embed threat modeling and security requirements into the AI development lifecycle, from data collection through deployment
• Build and maintain guardrails, monitoring, and detection controls for production AI systems, flagging anomalous model behavior and unauthorized data access
• Review third‑party AI tools, APIs, and vendors, including LLM providers, before integration, and lead incident response for AI‑related security events
• Advise on standards for secure and responsible AI use, validate access controls, encryption, and data segmentation, and use AI tools to accelerate security testing while modeling responsible use

Requirements

• Bachelor's degree and 5+ years in security engineering or application security, including hands‑on experience securing AI/ML systems or LLM‑based applications
• Deep knowledge of AI/ML security risks such as the OWASP Top 10 for LLMs, adversarial ML, and data poisoning, with proven ability to test for and mitigate them
• Experience with SAST/DAST, vulnerability scanning, and comfort scripting in Python or a comparable language
• Understanding of cloud infrastructure such as AWS, Azure, or GCP and how AI/ML workloads are deployed and secured within it
• Clear communication skills and comfort operating in a fast‑paced, evolving environment

Nice to have

• Experience securing systems in regulated healthcare or life sciences environments (HIPAA, HITRUST)
• Familiarity with LLM security frameworks such as MITRE ATLAS, Garak, or promptfoo
• Security certifications such as OSCP, GCIH, or CISSP, and red‑team experience

Benefits and work setup

• Remote‑first within the US, with a one‑time home office stipend and monthly Wi‑Fi reimbursement, plus flexible scheduling and core collaboration hours
• Competitive compensation, comprehensive medical, dental, and vision coverage with HSA/FSA contributions, 401(k) with company match, flexible PTO, 17 company holidays, paid sick and parental leave, and an annual company offsite