AI Security Engineer

Interra Health is a fast-growing healthcare technology company transforming how providers and patients navigate the prescription journey. Formed through the merger of DoseSpot, Arrive Health, and pVerify, Interra Health delivers trusted eligibility, real-time coverage and pricing insights, prescribing tools, and pharmacy transparency at the point of care—helping providers make informed decisions and patients access the right medications with greater clarity and affordability.

Interra Health is expanding its use of artificial intelligence and machine learning across a fast-moving, highly regulated healthcare market. As an AI Security Engineer on the Security Engineering team, reporting to the Lead Security Engineer, you will help secure the models, data pipelines, and AI solutions.

This role is hands-on and technical: you will assess AI systems for vulnerabilities, build guardrails against risks like prompt injection and data leakage, and partner with Engineering and Data & Analytics to bake security into how AI is designed and shipped. You will independently assess and resolve AI security risks across multiple workflows, escalating complex or high-impact issues to senior security leadership as appropriate. The right person is genuinely curious about how AI systems can fail, and wants to build the guardrails before something goes wrong, not after.

WHAT YOU'LL DO

• Lead security assessments of AI/ML models, data pipelines, and AI-enabled applications, identifying vulnerabilities such as prompt injection, model inversion, data poisoning, and adversarial inputs.

• Partner with Data & Analytics and Engineering to embed security requirements and threat modeling into the AI development lifecycle, from data collection through model deployment.

• Build and maintain guardrails, monitoring, and detection controls for AI systems in production, flagging anomalous model behavior and unauthorized data access.

• Conduct security reviews of third-party AI tools, APIs, and vendors, such as LLM providers, before they are integrated into Interra Health.

• Lead incident response for AI-related security events, including investigating suspicious model outputs or unexpected data exposure.

• Design and advise on standards for the secure, responsible use of AI, including data handling practices for training and inference.

• Test and validate access controls, encryption, and data segmentation for AI systems.

• Use AI tools to accelerate security testing, code review, and threat research, while modeling responsible AI use for the broader engineering organization.

• Stay current on the evolving AI threat landscape and translate emerging risks, such as jailbreaks and model-supply-chain risks, into practical mitigations.

• Document findings, risk assessments, and remediation plans clearly for both technical and non-technical stakeholders.

WHAT YOU'LL BRING

• 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 (including the OWASP Top 10 for LLMs, adversarial ML, and data poisoning) and proven ability to test for and mitigate them.

• Hands-on experience with security tooling, including SAST/DAST and vulnerability scanning, and comfort scripting in Python or a similar language.

• Understanding of cloud infrastructure (AWS, Azure, or GCP) and how AI/ML workloads are deployed and secured within it.

• Clear communicator who can translate technical risk into terms non-security stakeholders understand.

• Comfort operating in a fast-paced, post-merger environment where systems, priorities, and structures are still evolving.

NICE TO HAVE

• Experience securing systems in a regulated healthcare or life sciences environment (e.g., HIPAA, HITRUST).

• Familiarity with LLM security frameworks and tools, such as MITRE ATLAS, Garak, or promptfoo.

• Security certifications such as OSCP, GCIH, or CISSP.

• Experience red-teaming or penetration-testing AI/ML systems specifically.

CORE COMPETENCIES

Knowledge & Application: Applies established security engineering methods and growing AI/ML security knowledge to assess and harden AI systems. Adapts existing frameworks to the specific risks of Interra Health's AI-enabled healthcare products.

Complexity & Problem Solving: Handles moderately complex security assessments and technical problems using established methods, escalating novel or ambiguous AI-risk scenarios to senior security engineering leadership.

Collaboration & Interaction: Works closely with Data & Analytics, Engineering, and the broader Security Engineering team. Communicates findings clearly within the team and to the stakeholders whose systems are being assessed.