DevSecOps Engineer (REMOTE)- Veterans Affairs
THUNDERYARD SOLUTIONS
RemoteRemote$125,000 - $145,000 a yearFull Time
Job Description
*Why Join?*
Are you ready to tackle the unique security challenges of *AI/ML systems*? We are looking for a *Security Engineer* to provide *Information Assurance (IA)* and *ATO expertise*, combined with a deep understanding of *DevSecOps* practices, to support the development and security of a *multi-tenant AI/MLOps platform*. In this role, you’ll help ensure the platform complies with *federal cybersecurity standards* (e.g., RMF, NIST), while also addressing security risks specific to *AI/ML workloads*, *multi-tenancy*, *model pipelines*, and *data governance*. Gain an opportunity to shape security solutions for cutting-edge AI-enabled systems in the cloud.
*Key Responsibilities:*
* Perform *security assessments* and execute *Risk Management Framework (RMF)* processes for a highly *multi-tenant AI/MLOps platform*, ensuring the system achieves and maintains *Authorization to Operate (ATO)*.
* Identify risks specifically associated with *AI/ML models*, *data pipelines*, and *training workflows*, and recommend secure configurations and policies.
* Work with DevOps and MLOps engineers to embed *DevSecOps* practices into all stages of the AI/ML lifecycle, including the deployment of secure CI/CD pipelines for model training, deployment, and monitoring.
* Define and validate security measures for *AI/ML model governance*, focusing on model security (e.g., poisoning defense), *data privacy*, and tenant isolation.
* Secure *multi-tenant cloud environments*, emphasizing the segmentation of workloads, proper implementation of least privilege, and identity and access management (IAM) for tenants.
* Leverage tools (e.g., Prisma Cloud, Twistlock) to secure *containerized workloads* for AI pipelines, and collaborate with development teams to remediate vulnerabilities in *AI models, libraries, or frameworks*.
* Monitor and test platform security using *vulnerability scanners*, network monitors, and advanced techniques for systems requiring compliance with *NIST 800-53* or other federal requirements.
* Work extensively with *SNOW CAM* to document security artifacts, maintain compliance evidence, and provide progress reports to stakeholders.
* Collaborate with data scientists, MLOps engineers, and platform teams to balance usability, performance, and security while upholding tenant protections.
*Qualifications:*
* *12+ years* in cybersecurity, with demonstrated experience in *performing A&A processes* and applying *NIST RMF* requirements to cloud-native environments.
* *12+ years* securing or working with *multi-tenant systems*, preferably for AI/ML platforms or data-intensive applications.
* Experience working with tools and technologies relevant to *AI/ML workloads*, such as containerized environments (Kubernetes, Docker) and *AI frameworks* (e.g., TensorFlow, PyTorch, or MLflow).
* Familiarity with the *unique security challenges* posed by *AI/ML pipelines*, including *data provenance, adversarial attacks, and secure model deployment*.
* Knowledge of *tenant isolation techniques*, such as network segmentation, user/group roles, and identity federation across tenants.
* Hands-on experience implementing *DevSecOps pipelines*, including infrastructure-as-code (IaC) tools such as Terraform or Ansible, and scripting languages (e.g., Python, Bash).
* Working knowledge of *AWS GovCloud*, *Azure Government*, or other cloud platforms with compliance-focused regions.
* Expertise with *vulnerability scanning* and *remediation tools* like Nessus, OWASP ZAP, or cloud-based security platforms.
* Prior experience with compliance standards, including *NIST SP 800-53*, *800-37*, *ISO/IEC 27001*, or similar frameworks.
*Preferred Qualifications:*
* Familiarity with *AI ethics, data privacy laws*, and how they intersect with security standards in *federal contracts*.
* Experience configuring secure environments for *model training and inference* workflows, addressing *data leakage, model drift*, or adversarial ML risks.
* Knowledge of *trusted AI principles*, mitigations for *model poisoning*, or practices for preventing *data reconstruction attacks* from AI system outputs.
* Hands-on knowledge of *encryption methods* for sensitive AI/ML data at rest and in transit (e.g., data lake security configurations or homomorphic encryption).
* Familiarity with *federated learning* and securing decentralized AI models shared by multiple stakeholders.
* Exposure to *Elasticsearch* or database security in high-performance environments
*Compensation:*
The salary is budgeted at $125,000-$145,000 annually, plus benefits. ThunderYard offers benefits including medical, dental and vision insurance, 401k matching, PTO, certification reimbursement and more.
*Vetting:*
Applicants selected will be subject to a government investigation and may need to meet eligibility requirements of the U.S. government client.
_ThunderYard Solutions is proud to be an Equal Opportunity Employer. We don’t just accept difference – we celebrate it, we support it, and we thrive on it for the benefit of our employees, our community, and our customers. All applicants will be considered for employment without discrimination of race, color, religion, or belief, national, social, or ethnic origin, sex, age, physical, mental, or sensory disability, HIV status, sexual orientation, gender identity and/or expression, marital, civil union, or domestic partnership status, protected veteran status, family medical history or genetic information._
Job Type: Full-time
Pay: $125,000.00 - $145,000.00 per year
Benefits:
* 401(k)
* 401(k) matching
* Dental insurance
* Employee assistance program
* Flexible schedule
* Health insurance
* Health savings account
* Paid time off
* Professional development assistance
* Referral program
* Vision insurance
Work Location: Remote
Are you ready to tackle the unique security challenges of *AI/ML systems*? We are looking for a *Security Engineer* to provide *Information Assurance (IA)* and *ATO expertise*, combined with a deep understanding of *DevSecOps* practices, to support the development and security of a *multi-tenant AI/MLOps platform*. In this role, you’ll help ensure the platform complies with *federal cybersecurity standards* (e.g., RMF, NIST), while also addressing security risks specific to *AI/ML workloads*, *multi-tenancy*, *model pipelines*, and *data governance*. Gain an opportunity to shape security solutions for cutting-edge AI-enabled systems in the cloud.
*Key Responsibilities:*
* Perform *security assessments* and execute *Risk Management Framework (RMF)* processes for a highly *multi-tenant AI/MLOps platform*, ensuring the system achieves and maintains *Authorization to Operate (ATO)*.
* Identify risks specifically associated with *AI/ML models*, *data pipelines*, and *training workflows*, and recommend secure configurations and policies.
* Work with DevOps and MLOps engineers to embed *DevSecOps* practices into all stages of the AI/ML lifecycle, including the deployment of secure CI/CD pipelines for model training, deployment, and monitoring.
* Define and validate security measures for *AI/ML model governance*, focusing on model security (e.g., poisoning defense), *data privacy*, and tenant isolation.
* Secure *multi-tenant cloud environments*, emphasizing the segmentation of workloads, proper implementation of least privilege, and identity and access management (IAM) for tenants.
* Leverage tools (e.g., Prisma Cloud, Twistlock) to secure *containerized workloads* for AI pipelines, and collaborate with development teams to remediate vulnerabilities in *AI models, libraries, or frameworks*.
* Monitor and test platform security using *vulnerability scanners*, network monitors, and advanced techniques for systems requiring compliance with *NIST 800-53* or other federal requirements.
* Work extensively with *SNOW CAM* to document security artifacts, maintain compliance evidence, and provide progress reports to stakeholders.
* Collaborate with data scientists, MLOps engineers, and platform teams to balance usability, performance, and security while upholding tenant protections.
*Qualifications:*
* *12+ years* in cybersecurity, with demonstrated experience in *performing A&A processes* and applying *NIST RMF* requirements to cloud-native environments.
* *12+ years* securing or working with *multi-tenant systems*, preferably for AI/ML platforms or data-intensive applications.
* Experience working with tools and technologies relevant to *AI/ML workloads*, such as containerized environments (Kubernetes, Docker) and *AI frameworks* (e.g., TensorFlow, PyTorch, or MLflow).
* Familiarity with the *unique security challenges* posed by *AI/ML pipelines*, including *data provenance, adversarial attacks, and secure model deployment*.
* Knowledge of *tenant isolation techniques*, such as network segmentation, user/group roles, and identity federation across tenants.
* Hands-on experience implementing *DevSecOps pipelines*, including infrastructure-as-code (IaC) tools such as Terraform or Ansible, and scripting languages (e.g., Python, Bash).
* Working knowledge of *AWS GovCloud*, *Azure Government*, or other cloud platforms with compliance-focused regions.
* Expertise with *vulnerability scanning* and *remediation tools* like Nessus, OWASP ZAP, or cloud-based security platforms.
* Prior experience with compliance standards, including *NIST SP 800-53*, *800-37*, *ISO/IEC 27001*, or similar frameworks.
*Preferred Qualifications:*
* Familiarity with *AI ethics, data privacy laws*, and how they intersect with security standards in *federal contracts*.
* Experience configuring secure environments for *model training and inference* workflows, addressing *data leakage, model drift*, or adversarial ML risks.
* Knowledge of *trusted AI principles*, mitigations for *model poisoning*, or practices for preventing *data reconstruction attacks* from AI system outputs.
* Hands-on knowledge of *encryption methods* for sensitive AI/ML data at rest and in transit (e.g., data lake security configurations or homomorphic encryption).
* Familiarity with *federated learning* and securing decentralized AI models shared by multiple stakeholders.
* Exposure to *Elasticsearch* or database security in high-performance environments
*Compensation:*
The salary is budgeted at $125,000-$145,000 annually, plus benefits. ThunderYard offers benefits including medical, dental and vision insurance, 401k matching, PTO, certification reimbursement and more.
*Vetting:*
Applicants selected will be subject to a government investigation and may need to meet eligibility requirements of the U.S. government client.
_ThunderYard Solutions is proud to be an Equal Opportunity Employer. We don’t just accept difference – we celebrate it, we support it, and we thrive on it for the benefit of our employees, our community, and our customers. All applicants will be considered for employment without discrimination of race, color, religion, or belief, national, social, or ethnic origin, sex, age, physical, mental, or sensory disability, HIV status, sexual orientation, gender identity and/or expression, marital, civil union, or domestic partnership status, protected veteran status, family medical history or genetic information._
Job Type: Full-time
Pay: $125,000.00 - $145,000.00 per year
Benefits:
* 401(k)
* 401(k) matching
* Dental insurance
* Employee assistance program
* Flexible schedule
* Health insurance
* Health savings account
* Paid time off
* Professional development assistance
* Referral program
* Vision insurance
Work Location: Remote