Senior AI Security Engineer

Jobtailor

Town of Florida (NY)

On-site

USD 120,000 - 180,000

Full time

10 days ago

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Job summary

Healthfirst is seeking an experienced security engineer to continuously monitor enterprise vulnerabilities and spearhead engineering solutions for securing Healthfirst infrastructure and AI-enabled apps.

You will conduct threat modeling, perform hands-on security testing of LLMs, RAG, and agentic AI, and collaborate with developers to implement robust security controls across cloud environments and CI/CD pipelines.

Qualifications

Technical Degree in Computer Science or Cyber Security 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.

Responsibilities

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

Skills

Security Engineering

Vulnerability Assessment

Application Security

AI Security Testing

Cloud Security

Threat Modeling

Penetration Testing

Security Architecture Reviews

Data Protection

CI/CD Integration

Infrastructure as Code

Python

Security Testing

Incident Response

Education

Technical Degree in Computer Science

Technical Degree in Cyber Security

Tools

Azure OpenAI

AWS Bedrock

Google Vertex AI

Terraform

Bicep

CloudFormation

DevSecOps

LLM

RAG

Vector Databases

Job description

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

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

Core Competencies

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.

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