Senior AI Security Engineer

Healthfirst

Healthfirst AI security engineer securing LLM, RAG, and agentic applications. Protecting PHI and PII through cloud security, threat modeling, and engineering controls.

Posted 8/25/2026full-timeNew York City • Florida, New York • 🇺🇸 United StatesSenior💰 $119,600 - $194,480 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in security engineering, vulnerability assessment, and application security, with a strong focus on AI-enabled applications and compliance with healthcare regulations. Proficient in developing security controls, conducting threat modeling, and implementing secure software development practices.

Highest-signal resume keywords

Security EngineeringVulnerability AssessmentApplication SecurityAI Security TestingCloud Security

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Threat ModelingPenetration TestingSecurity Architecture ReviewsProgramming in PythonCI/CD IntegrationInfrastructure as CodeData ProtectionAPI SecuritySecurity TestingIncident Response

Tools & Technologies

Azure OpenAIAWS BedrockGoogle Vertex AITerraformBicepCloudFormationDevSecOpsLLMRAGVector Databases

Certifications & Qualifications

Technical Degree in Computer ScienceTechnical Degree in Cyber Security

Industry Keywords

PHIPIIHealthcare RegulationsOWASPMITRE ATLASNIST AI Security GuidanceSensitive DataAgentic AI SecurityMCP Security ConsiderationsSoftware Supply-Chain Security

Tech Stack

Tools & technologies

AWSAzureCloudCyber SecurityPythonTerraform

About the role

Key responsibilities & impact

Continuously monitor enterprise vulnerabilities and develop engineering solutions to improve Healthfirst infrastructure security
Perform security architecture reviews and threat modeling for AI-enabled applications
Conduct hands-on security testing of LLM, RAG, and agentic AI solutions
Identify vulnerabilities such as prompt injection, sensitive-data exposure, insecure retrieval, excessive permissions, unsafe tool use, and authorization weaknesses
Assess security risks associated with AI agents, APIs, model integrations, vector databases, and third-party AI services
Partner with developers and AI engineering teams to design and implement practical security controls
Develop reusable security patterns and guardrails for common AI architectures
Build or automate security tests and tools for evaluating AI applications
Protect PHI, PII, credentials, and other sensitive information used by AI systems
Evaluate emerging AI security threats and translate findings into engineering guidance
Support application security and secure AI development practices
Ensure AI systems handling sensitive healthcare and enterprise information have appropriate security and privacy controls
Assess sensitive-information flows through prompts, models, APIs, retrieval systems, embeddings, vector stores, logs, agents, and downstream systems
Partner with privacy, compliance, legal, risk, and AI governance teams to translate requirements into technical controls
Support secure and responsible AI adoption consistent with organizational policies and healthcare and regulatory requirements
Perform additional duties as required

Requirements

What you’ll need

Technical Degree in Computer Science or Cyber Security and/or equivalent work experience
Prior Cyber Security work experience
Experience in security engineering, vulnerability assessment, threat hunting, and incident response
High School diploma or GED from an accredited institution
5+ years of experience in application security, product security, security engineering, cloud security, offensive security, or a related technical security discipline (preferred)
Strong understanding of application and API security, authentication, authorization, identity, data protection, and secure software development
Hands-on experience with security architecture reviews, threat modeling, vulnerability assessment, penetration testing, or security testing
Working knowledge of LLMs, model APIs, RAG, vector databases, and AI agents
Understanding of AI security risks including prompt injection, data leakage, insecure output handling, excessive agency, and unsafe tool or API access
Programming or scripting experience, preferably Python
Experience working with cloud-based applications and services
Experience securing production generative AI or LLM applications
Experience with AI/LLM security testing or red teaming
Familiarity with agentic AI security, MCP security considerations, OWASP LLM/GenAI guidance, MITRE ATLAS, or NIST AI security guidance
Experience with Azure OpenAI, AWS Bedrock, Google Vertex AI, or comparable AI platforms
Experience working with PHI, PII, or other sensitive data in a regulated environment
Experience integrating security testing into CI/CD or DevSecOps workflows
Experience with software supply-chain security and SBOM practices
Experience designing secure tool and API consumption patterns for agentic AI
Experience reviewing or implementing Infrastructure as Code and cloud/AI infrastructure security controls
Experience with Terraform, Bicep, CloudFormation, or comparable frameworks preferred

Benefits

Comp & perks

Medical, dental and vision coverage
Incentive and recognition programs
Life insurance
401k contributions
Competitive compensation and benefits package