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Position Overview

We are seeking a senior-level AI/ML Security Engineer to help establish and mature security practices across machine learning, generative AI, and agentic development environments.
This is a Hybrid onsite engagement, located in NJ 3 days a week, ideally paying on a W2 hourly basis.

This role sits at the intersection of cybersecurity, software engineering, MLOps, and emerging AI technologies. The engineer will be responsible for identifying risks within AI/ML systems and building practical security controls into the platforms, pipelines, and development processes used to create and deploy them.

A major focus will be securing the rapidly evolving use of LLMs, AI coding assistants, autonomous agents, RAG architectures, and agentic software-development workflows. The ideal candidate is highly technical and capable of both defining security strategy and implementing controls through code and automation.

Key Responsibilities

• Design and implement security controls throughout AI/ML and MLOps pipelines, including data ingestion, model development, validation, storage, deployment, and inference.

• Assess security risks associated with machine learning models, LLM applications, AI agents, datasets, prompts, and AI-enabled applications.

• Evaluate the security of AI coding assistants, coding agents, autonomous agents, and agentic workflows used within software engineering organizations.

• Establish security guardrails for AI-assisted development platforms, agent orchestration frameworks, and autonomous development pipelines.

• Help develop an enterprise framework for securing the Agentic Development Lifecycle (ADLC), incorporating threat modeling, secure development requirements, testing, deployment controls, approvals, and continuous monitoring.

• Evaluate AI Security Posture Management (AI-SPM) capabilities and establish processes for discovering, classifying, prioritizing, and remediating AI-related security risks.

• Assess emerging attacks against LLMs, frontier AI models, and autonomous agents and translate those risks into preventative and detective security controls.

• Develop and maintain automation and security capabilities using Python and CI/CD technologies.

• Integrate model and AI security scanning into development pipelines as part of a shift-left security strategy.

• Analyze model-scanning and vulnerability-assessment results and partner with engineering teams on remediation.

• Assess model inference and deployment architectures with consideration for security, performance, scalability, and resource utilization.

• Evaluate security surrounding agent sandboxes, runtime environments, tool access, permissions, agent-to-tool communication, and execution workflows.

• Establish controls governing autonomous agent behavior, including permissions, approval mechanisms, runtime restrictions, secrets management, and data-access boundaries.

• Partner closely with application security, platform engineering, software development, data science, and machine learning teams.

• Research emerging AI security threats and recommend improvements to enterprise security architecture and engineering practices.

Required Experience

• 8+ years of experience across software engineering, cybersecurity, application security, platform engineering, or related technical disciplines.

• 5+ years of hands-on software engineering or development experience.

• Strong understanding of AI/ML security, GenAI security, and agentic AI risks.

• Hands-on experience building or supporting MLOps pipelines and model deployment environments.

• Experience with platforms such as MLflow, Kubeflow, AWS SageMaker, or comparable MLOps technologies.

• Strong Python programming and automation skills.

• Strong understanding of modern CI/CD pipelines and secure software-development practices.

• Experience incorporating security testing or scanning into automated development pipelines.

• Hands-on familiarity with AI-assisted development tools such as GitHub Copilot, Claude Code, Cursor, Windsurf, Microsoft Copilot, or similar platforms.

• Experience using AI-assisted engineering techniques across one or more languages such as Python, Java, JavaScript, C#, .NET, or Go.

• Strong understanding of LLMs, AI agents, autonomous workflows, RAG architectures, tool-calling systems, and agent orchestration.

• Experience assessing the security implications of agent runtime environments, sandboxing, tool permissions, and autonomous execution.

• Ability to assess and prioritize risks involving AI models, prompts, datasets, agents, and AI-enabled applications.

• Strong understanding of AI/ML attack vectors, including:

  • Prompt injection

  • Data and model poisoning

  • Model extraction and inversion

  • Adversarial inputs and examples

  • AI/ML supply-chain vulnerabilities

  • Excessive agent permissions and unsafe tool usage

  • Sensitive-data exposure

• Familiarity with industry guidance such as the OWASP security frameworks for LLM and machine-learning applications.

• Experience with model vulnerability scanning, model security assessment, or similar AI security tooling.

• Understanding of common ML model and serialization formats such as Pickle, TensorFlow formats, and SafeTensors.

• Familiarity with both structured and unstructured data environments, including SQL databases, data warehouses, object storage, and NoSQL platforms.

• Understanding of cloud, container, microservices, and application security principles.

• Excellent analytical and problem-solving skills.

Technical Environment

Experience with several of the following technologies would be valuable:

AI/ML & Data

• MLflow

• Kubeflow

• SageMaker

• Databricks

• RAG architectures

• LLM and agent frameworks

Development

• Python

• Java

• C# / .NET

• JavaScript

• Go

• REST APIs

• Microservices

DevSecOps / CI/CD

• Git

• Bitbucket

• Jenkins

• Artifactory

• Nexus

• SonarQube

• Snyk

• Jira

• Automated security scanning

Preferred Background

• Previous experience as a software engineer or software architect before moving into security.

• Experience implementing model-scanning capabilities across an enterprise ML development environment.

• Experience defining security architecture for GenAI or agentic AI platforms.

• Familiarity with AI Security Posture Management concepts and tooling.

• Strong knowledge of secure design patterns for cloud-native and containerized applications.

• Experience working within Agile engineering organizations.

• Experience communicating emerging technical risks to engineering leadership and non-security stakeholders.

Education & Certifications

• Bachelor's degree in Computer Science, Cybersecurity, Computer Engineering, Information Systems, or a related technical discipline, or equivalent professional experience.
• Security certifications such as CISSP, CSSLP, CEH, GCIA, GPEN, or GWAPT are beneficial but not required.

Ampcus Inc. is a certified global provider of a broad range of Technology and Business consulting services. We are in search of a highly motivated candidate to join our talented Team.

 

Job Title: Senior Cloud Security Engineer

Location(s): Warren, NJ


About the Role
We are seeking an experienced Senior Cloud Security Engineer to own cloud security remediation, hardening, and governance across the cloud environment.

This is a hands-on engineering role focused on implementing permanent security fixes, addressing recurring vulnerabilities, and ensuring security controls are enforced through automation and secure architecture.

The ideal candidate will have extensive Azure security experience, strong Microsoft Entra ID expertise, and a proven ability to translate security recommendations into sustainable engineering solutions.

Key Responsibilities
Security Remediation and Recurrence Prevention

• Own the complete lifecycle of security findings and recommendations, from triage and remediation through verification and closure.
• Address findings identified by security teams, Microsoft Defender for Cloud, and other security tools.
• Perform root-cause analysis of recurring security issues and implement permanent solutions.
• Develop policy-as-code, automated guardrails, and secure baselines to prevent recurring vulnerabilities.
• Track remediation SLAs and report on security risk reduction and cloud security posture improvements.

Identity and Authentication Security

• Secure and govern modern authentication protocols, including OIDC, OAuth 2.0 with PKCE, JWT validation, and mutual TLS (mTLS).
• Administer and harden Microsoft Entra ID, including application registrations, Enterprise Applications, permissions, consent governance, service principals, and managed identities.
• Implement credential and secret management practices and enforce least-privilege access.
• Design, implement, and continuously optimize Conditional Access policies.

Cloud Security Engineering and Governance

• Develop and enforce cloud security guardrails using Azure Policy and Terraform.
• Maintain secure-by-default Infrastructure-as-Code (IaC) baselines.
• Identify, monitor, and remediate cloud configuration drift.
• Manage Microsoft Defender for Cloud, improve secure scores, and remediate security recommendations.
• Support Cloud Security Posture Management (CSPM) initiatives.
• Contribute to security governance, including standards, control definitions, exception management, and audit evidence.

Administrative Portal and Privileged Access Security

• Secure cloud and SaaS administrative portals, including Azure, Microsoft 365, identity providers, and other cloud administration consoles.
• Enforce MFA and strengthen privileged access management.
• Implement Privileged Identity Management (PIM), just-in-time access, and role minimization.
• Establish and maintain secure break-glass access procedures.

AI Security

• Implement security controls for AI workloads, services, and AI agents.
• Secure agent and workload identities and enforce appropriate tool and permission scoping.
• Address data exposure, prompt injection, and emerging AI security risks.
• Apply security best practices to AI-enabled applications and agentic systems.

Required Qualifications

• 9+ years of experience in cloud security or security engineering, with extensive hands-on Microsoft Azure experience.
• Strong expertise in Microsoft Entra ID, including application registrations, Enterprise Applications, permissions, consent governance, and Conditional Access.
• Solid understanding of modern authentication protocols, including OIDC, OAuth 2.0/PKCE, JWT, and mTLS.
• Hands-on experience with Terraform and Azure Policy for policy-as-code and automated security guardrails.
• Experience with Microsoft Defender for Cloud and Cloud Security Posture Management (CSPM).
• Demonstrated experience identifying root causes and permanently resolving security findings rather than applying temporary fixes.
• Working knowledge of AI, AI agents, and AI security considerations.

Preferred Qualifications

• Experience with multi-cloud environments, including AWS and GCP.
• Relevant certifications such as Microsoft SC-100, AZ-500, SC-300, or CISSP.
• Experience with CI/CD pipeline security, secrets management, and SIEM/SOAR platforms.
• Scripting and automation experience using PowerShell and Python.
• Hands-on experience securing LLM-based applications or agentic systems in production.

Ampcus is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veterans or individuals with disabilities.

We are seeking a Lead MLSecOps Security Engineer. 

What You’ll Do:

• Design, implement, and maintain secure ML pipelines for AI/ML model evaluation, validation, deployment, and inference.
• Assess and mitigate security risks throughout the ML lifecycle, including data ingestion, model storage, and deployment.
• Evaluate, secure, and govern AI coding agents, autonomous agents, and agentic workflows used throughout the software development lifecycle.
• Define and implement security guardrails for AI-assisted software development platforms, agent orchestration frameworks, and autonomous development pipelines.
• Develop and operationalize an Agentic Development Lifecycle (ADLC) framework that incorporates security requirements, threat modeling, testing, deployment governance, and continuous security monitoring.
• Evaluate AI Security Posture Management (AI-SPM) capabilities and establish processes for identifying, categorizing, prioritizing, and remediating risks associated with AI assets, agents, prompts, datasets, and AI-enabled applications.
• Assess emerging threats against frontier AI models and agentic systems and recommend preventative and detective security controls to reduce enterprise risk.
• Develop and maintain code for AI/ML pipelines using Python and CICD, ensuring robust security controls and compliance with best practices.
• Institutionalize security scanning of AI/ML models in line with shift left strategy; interpret results and remediate identified issues.
• Evaluate and optimize model inference deployment strategies, balancing security, performance, and resource utilization.
• Stay current on top vulnerabilities affecting Machine Learning Models, Large Language Models (LLMs), and AI agents, such as prompt injection, data poisoning, model theft, and adversarial attacks.
• Collaborate with data scientists, ML engineers, and security teams to drive adoption of secure ML practices.
• Establish strong partnership with key stakeholders in technology and product organizations.
• Perform other duties as required.

Experience You'll Need:

• Hands-on experience with MLOps pipelines and model deployment tools (e.g., Kubeflow, MLflow, SageMaker).
• Strong programming skills in Python and CICD for automation and pipeline development.
• Hands-on experience with major AI coding assistants and coding agents such as GitHub Copilot, Microsoft Copilot, Cursor, Claude Code, Windsurf, or similar AI-assisted development platforms.
• Experience using AI-driven development techniques across multiple programming languages including Python, Java, JavaScript, C#, .NET, Go, or similar technologies.
• Strong understanding of agentic architectures, AI agents, autonomous workflows, Retrieval-Augmented Generation (RAG), and associated security considerations.
• Experience assessing Agent Sandboxes, agent runtime environments, agent-to-tool communications, and agent execution workflows.
• Understanding of security limitations and control mechanisms governing agent behavior, including permissions, approval workflows, runtime controls, and data protection guardrails.
• Ability to identify, categorize, prioritize, and operationalize risks associated with AI assets, models, prompts, datasets, agents, and AI-enabled applications.
• Deep understanding of Agentic Development Lifecycle (ADLC) principles and integration of security controls throughout planning, development, testing, deployment, and operations.
• Knowledge of frontier AI model cybersecurity programs and the ability to reason about layered controls that mitigate AI-driven cyber attacks, adversarial ML threats, model and agent abuse.
• Familiarity with structured (SQL, data warehouses) and unstructured (object storage, NoSQL) data systems.
• Familiarity with Databricks
• Experience with ML security tools for model scanning and vulnerability assessment.
• Knowledge of top OWASP AI/ML vulnerabilities, including:

- Prompt injection
- Data and model poisoning
- Model extraction and inversion
- Adversarial example attacks
- Supply chain risks in ML components

• Strong communication skills and ability to document and explain Cybersecurity and AI/ML security controls to technical and non-technical stakeholders.
• Understanding of AL/ML model formats such as pickle, tensorflow, safetensors
• Experience in rolling out model scanning solution as part of model development.
• Understanding CI/CD pipelines covering source control, integration, and deployment (ex: Bitbucket, Jenkins, JIRA, Artifactory, Nexus, SonarQube, git, Snyk scanner).
• Previous software engineering/architecture experience (Java, C#, .Net, JavaScript, Python) preferred.
• Strong analytical/problem solving skills and cross functional knowledge across multiple development and security disciplines.
• Experience with development of RESTful web services preferred.
• Understanding of advanced iterative Agile, Cloud and Container Security, GenAI Security
• Exceptional problem-solving skill
• Excellent communication and presentation skills
• Ability to be a good team player as part of remote teams
• Self-motivated with positive attitude
• Should be able to work independently.

Qualifications:

• Bachelor's degree in computer science, Information / Cyber Security, Computer Systems Engineering, Computer Information Systems or equivalent education and experience required
• Eight years or more experience in various IT or cybersecurity roles, with five or more years of experience specifically in software engineering roles.
• Deep knowledge and understanding of AI/ML and Agentic Security and related risks
• Candidate should be very thorough in internet technologies and highly versed with web development best practices.
• Strong analytical/problem solving skills and cross functional knowledge across multiple development and security disciplines.
• Ability to communicate security-related concepts to a broad range of technical and non-technical stakeholders.
• Understanding of advanced iterative Agile and container & cloud security
• Familiarity with micro-services architecture and Design Patterns
• Excellent analytic skills, including qualitative and quantitative data analysis to support and defend data-driven decision-making regarding system threats, vulnerabilities, and risk
• Any of the following are a plus but not necessary: CEH, CISSP, CSSLP, GCIA, GPEN, GWAPT

Information Security Engineer - Audubon, PA (Onsite) - Full Time - $110,000 Per Year

Join our team as an Information Security Engineer in the Audubon, PA region, where you'll work full time to enhance our security infrastructure. You'll be responsible for implementing and managing security controls, investigating security incidents, and ensuring data protection across various cloud platforms. This role requires expertise in identity protection, cloud threat detection, and incident response.

Key Responsibilities

• Design and maintain security controls across various cloud platforms.
• Lead security monitoring and incident response efforts.
• Develop and optimize threat detection and response workflows.
• Enhance enterprise identity security and privileged access management.
• Collaborate with stakeholders during security investigations and remediation activities.

Qualifications

• Bachelor's degree in Information Security or related field.
• Certification in cloud security or equivalent hands-on experience.
• Advanced proficiency in security monitoring and incident response.
• Strong scripting skills in languages such as Python or PowerShell.
• Experience with identity and access management technologies.

Core Technologies

SIEM | EDR | SOAR | Vulnerability Management Tools | Python | PowerShell | Cloud Security | Zero Trust Architecture

Contact Authorization

By applying for this job, you agree to receive AI-generated calls, text messages, and/or emails from Mitchell Martin Inc and its affiliates and contracted partners at various frequency through traditional and automated methods. Message and data rates may apply for texts. Carriers are not liable for delayed or undelivered messages. You can access our privacy policy on our web site or here ((url removed)).

Onboarding Expectations

Learn more about our Onboarding Process on our web site or here ((url removed))

EEO Statement

Learn more about our EEO policy here ((url removed))

#LI-JG3

Job Title: Senior Cyber Security Engineer
Location: On site at either Limerick / Pottstown, PA (preferred) or Peach Bottom / Delta, PA 
Duration: 12 months of contract with possible extension 

Job Description: 
Seeking a Senior Cyber Security Engineer to lead cybersecurity and network infrastructure initiatives in a nuclear utility environment. This role will provide technical leadership for solution design, deployment, migration, operational support, regulatory readiness, incident response, and disaster recovery. The engineer will work independently, partner with business and IT stakeholders, support onsite implementations, and travel as needed.

Must have a thorough understanding and strong demonstration of network infrastructure, rewall, intrusion detection systems, Security Information and Event Management (SIEM), technologies and how they strategically intersect with business requirements.

Core Responsibilities

• Lead cybersecurity and network infrastructure projects, deployments, migrations, and implementation activities.
• Develop and maintain technical documentation, processes, standards, and operational support procedures.
• Design, integrate, optimize, and support secure, reliable IT and cybersecurity solutions aligned with business requirements.
• Provide technical leadership for audits, regulatory reviews, incident response, disaster recovery, and cybersecurity program activities.
• Partner with project managers, business stakeholders, and IT teams; communicate complex technical information clearly and mentor others.

Required Qualifications

• Nuclear utility experience.
• U.S. Residence within one hour of Pottstown or Delta, Pennsylvania, with required onsite presence.
• Bachelor’s degree in Cyber Security, Information Technology, Computer Science, or a related field plus 5–8 years of relevant networking and cybersecurity experience; or 9–12 years of equivalent education and experience.
• Advanced knowledge of Windows and Linux operating systems, command-line tools, IP switching and routing, enterprise networking, and network security.
• Hands-on expertise with SIEM platforms such as Splunk, Nitro, or Industrial Defender and firewalls such as Cisco or Check Point.
• Strong knowledge of enterprise cybersecurity practices, including policy development, application and information security, network security, operational security, incident response, disaster recovery, and end-user education.
• Strong communication, change management, and project leadership skills; ability to work autonomously, adapt to changing priorities, and travel as needed.

Preferred Certifications

• CISSP
• CCNP
• PMP

Role: Senior Cloud Security Engineer
Location: Warren, NJ - Onsite 


About the Role

We’re hiring a Senior Cloud Security Engineer to serve as the dedicated owner of cloud security remediation and hardening across our environment.
Our organization already has an established security team that identifies risks and issues recommendations. This role does not sit on that team. Instead, you are the engineer who turns those recommendations into durable, well-architected fixes—and, just as importantly, makes sure the same findings don’t come back.
This is a hands-on engineering role, not an advisory one. Success means a measurably more secure environment, a shrinking backlog of recurring findings, and security controls that are enforced by design rather than by manual effort or one-off patches.

What You’ll Do
Remediation & recurrence prevention (the core of this role)
• Own the full lifecycle of security findings and recommendations—whether they come from the security team, Microsoft Defender for Cloud, or other tooling—through triage, remediation, verification, and closure.
• Root-cause recurring issues and implement systemic fixes (policy-as-code, automated guardrails, secure baselines) so the same findings don’t reappear quarter after quarter.
• Track remediation SLAs and report on risk reduction and posture trends over time.
Identity & authentication
• Secure and govern modern authentication flows across the estate: OIDC, OAuth 2.0 with PKCE, JWT validation and handling, and mTLS.
• Administer and harden Microsoft Entra ID (Azure Entra): app registrations and Enterprise Application permissions, consent governance, service principals and managed identities, credential and secret hygiene, and least-privilege scoping.
• Design, implement, and continuously tune Conditional Access policies.
Cloud security engineering & governance
• Build and enforce guardrails using Azure Policy and Terraform; maintain secure-by-default infrastructure-as-code baselines and detect/remediate configuration drift.
• Operate Microsoft Defender for Cloud—drive secure-score improvement, remediate recommendations, and manage cloud security posture (CSPM).
• Contribute to security governance: standards, control definitions, exception handling, and audit evidence.

Admin portal & privileged access security
• Secure all cloud and SaaS administrative portals - Azure and other admin consoles (e.g., Microsoft 365 admin, identity providers, and any additional cloud platforms in use).
• Strengthen privileged access: MFA enforcement, Privileged Identity Management (PIM) / just-in-time elevation, role minimization, and break-glass procedures.
AI security
• Apply security controls to AI workloads, services, and AI agents: agent and workload identities, tool and permission scoping, data-exposure and prompt-injection risk, and emerging AI security best practices.
What You Bring (Required)
• 9+ years in cloud security or security engineering, with deep, hands-on Azure experience.
• Strong, hands-on Microsoft Entra ID expertise: app registrations, Enterprise Apps, permissions and consent, and Conditional Access.
• Solid working knowledge of modern authentication: OIDC, OAuth 2.0 / PKCE, JWT, and mTLS.
• Proficiency with Terraform and Azure Policy for policy-as-code and automated guardrails.
• Experience with Microsoft Defender for Cloud and cloud security posture management.
• A demonstrable track record of root-causing and permanently closing security findings—not just patching them.
• Working understanding of AI, AI agents, and AI security considerations.

Nice to Have
• Multi-cloud exposure (AWS, GCP).
• Relevant certifications (e.g., Microsoft SC-100, AZ-500, SC-300; CISSP).
• Experience with CI/CD pipeline security, secrets management, and SIEM/SOAR.
• Scripting/automation (PowerShell, Python).
• Hands-on experience securing LLM-based or agentic systems in production.

Position Overview

We are seeking a senior-level AI/ML Security Engineer to help establish and mature security practices across machine learning, generative AI, and agentic development environments.
This is a Hybrid onsite engagement, located in NJ 3 days a week, ideally paying on a W2 hourly basis.

This role sits at the intersection of cybersecurity, software engineering, MLOps, and emerging AI technologies. The engineer will be responsible for identifying risks within AI/ML systems and building practical security controls into the platforms, pipelines, and development processes used to create and deploy them.

A major focus will be securing the rapidly evolving use of LLMs, AI coding assistants, autonomous agents, RAG architectures, and agentic software-development workflows. The ideal candidate is highly technical and capable of both defining security strategy and implementing controls through code and automation.

Key Responsibilities

• Design and implement security controls throughout AI/ML and MLOps pipelines, including data ingestion, model development, validation, storage, deployment, and inference.

• Assess security risks associated with machine learning models, LLM applications, AI agents, datasets, prompts, and AI-enabled applications.

• Evaluate the security of AI coding assistants, coding agents, autonomous agents, and agentic workflows used within software engineering organizations.

• Establish security guardrails for AI-assisted development platforms, agent orchestration frameworks, and autonomous development pipelines.

• Help develop an enterprise framework for securing the Agentic Development Lifecycle (ADLC), incorporating threat modeling, secure development requirements, testing, deployment controls, approvals, and continuous monitoring.

• Evaluate AI Security Posture Management (AI-SPM) capabilities and establish processes for discovering, classifying, prioritizing, and remediating AI-related security risks.

• Assess emerging attacks against LLMs, frontier AI models, and autonomous agents and translate those risks into preventative and detective security controls.

• Develop and maintain automation and security capabilities using Python and CI/CD technologies.

• Integrate model and AI security scanning into development pipelines as part of a shift-left security strategy.

• Analyze model-scanning and vulnerability-assessment results and partner with engineering teams on remediation.

• Assess model inference and deployment architectures with consideration for security, performance, scalability, and resource utilization.

• Evaluate security surrounding agent sandboxes, runtime environments, tool access, permissions, agent-to-tool communication, and execution workflows.

• Establish controls governing autonomous agent behavior, including permissions, approval mechanisms, runtime restrictions, secrets management, and data-access boundaries.

• Partner closely with application security, platform engineering, software development, data science, and machine learning teams.

• Research emerging AI security threats and recommend improvements to enterprise security architecture and engineering practices.

Required Experience

• 8+ years of experience across software engineering, cybersecurity, application security, platform engineering, or related technical disciplines.

• 5+ years of hands-on software engineering or development experience.

• Strong understanding of AI/ML security, GenAI security, and agentic AI risks.

• Hands-on experience building or supporting MLOps pipelines and model deployment environments.

• Experience with platforms such as MLflow, Kubeflow, AWS SageMaker, or comparable MLOps technologies.

• Strong Python programming and automation skills.

• Strong understanding of modern CI/CD pipelines and secure software-development practices.

• Experience incorporating security testing or scanning into automated development pipelines.

• Hands-on familiarity with AI-assisted development tools such as GitHub Copilot, Claude Code, Cursor, Windsurf, Microsoft Copilot, or similar platforms.

• Experience using AI-assisted engineering techniques across one or more languages such as Python, Java, JavaScript, C#, .NET, or Go.

• Strong understanding of LLMs, AI agents, autonomous workflows, RAG architectures, tool-calling systems, and agent orchestration.

• Experience assessing the security implications of agent runtime environments, sandboxing, tool permissions, and autonomous execution.

• Ability to assess and prioritize risks involving AI models, prompts, datasets, agents, and AI-enabled applications.

• Strong understanding of AI/ML attack vectors, including:

  • Prompt injection

  • Data and model poisoning

  • Model extraction and inversion

  • Adversarial inputs and examples

  • AI/ML supply-chain vulnerabilities

  • Excessive agent permissions and unsafe tool usage

  • Sensitive-data exposure

• Familiarity with industry guidance such as the OWASP security frameworks for LLM and machine-learning applications.

• Experience with model vulnerability scanning, model security assessment, or similar AI security tooling.

• Understanding of common ML model and serialization formats such as Pickle, TensorFlow formats, and SafeTensors.

• Familiarity with both structured and unstructured data environments, including SQL databases, data warehouses, object storage, and NoSQL platforms.

• Understanding of cloud, container, microservices, and application security principles.

• Excellent analytical and problem-solving skills.

Technical Environment

Experience with several of the following technologies would be valuable:

AI/ML & Data

• MLflow

• Kubeflow

• SageMaker

• Databricks

• RAG architectures

• LLM and agent frameworks

Development

• Python

• Java

• C# / .NET

• JavaScript

• Go

• REST APIs

• Microservices

DevSecOps / CI/CD

• Git

• Bitbucket

• Jenkins

• Artifactory

• Nexus

• SonarQube

• Snyk

• Jira

• Automated security scanning

Preferred Background

• Previous experience as a software engineer or software architect before moving into security.

• Experience implementing model-scanning capabilities across an enterprise ML development environment.

• Experience defining security architecture for GenAI or agentic AI platforms.

• Familiarity with AI Security Posture Management concepts and tooling.

• Strong knowledge of secure design patterns for cloud-native and containerized applications.

• Experience working within Agile engineering organizations.

• Experience communicating emerging technical risks to engineering leadership and non-security stakeholders.

Education & Certifications

• Bachelor's degree in Computer Science, Cybersecurity, Computer Engineering, Information Systems, or a related technical discipline, or equivalent professional experience.
• Security certifications such as CISSP, CSSLP, CEH, GCIA, GPEN, or GWAPT are beneficial but not required.

AWS Cloud Security Guardrails Engineer (TS/SCI)
Location: Herndon, VA or Washington, DC (on-site)
Clearance: Active TS/SCI Type: Full-time
Overview
A federal program team building secure AWS platforms is adding a security engineer who can help set the security design from day one. The work centers on turning security requirements into usable identity, encryption, and observability guardrails that development teams can build on without second-guessing.
What You Will Do

• Build reusable security guardrails into deployment pipelines in partnership with engineering teams.
• Assess cloud architectures and infrastructure code for security gaps.
• Create and refine AWS IAM policies, KMS encryption controls, and centralized logging designs.
• Help assemble evidence and documentation for security assessments.

What You Bring

• 5 or more years of engineering experience, at least 3 of them hands-on in AWS.
• Deep working knowledge of AWS IAM, KMS, logging, and cloud security architecture.
• A track record of checking technical builds against defined security requirements.
• Ability to work well in a closely controlled operating environment.

Nice to Have

• Security for infrastructure as code, or automated policy validation.
• Hands-on support of formal security authorization efforts.
• AWS Professional or Specialty certification. Security+ or CISSP is a plus.

Additional Requirements

• Current, active TS/SCI. You must also qualify for SCI indoctrination and any program-level access approvals the customer requires.
• U.S. citizenship is required under the terms of the government contract.
• You must live within a reasonable daily commute of the secure site in Herndon, VA or Washington, DC.
• Full-time and fully on-site in an accredited secure facility, with occasional visits to approved customer sites. Remote work is not an option.

Duties May Include:

• Apply RMF processes to support system Assessment & Authorization (A&A), including control selection, implementation, assessment, and continuous monitoring
• Develop, review, and maintain security documentation such as SSPs, POA&Ms, SARs, and ATO artifacts in tools such as XACTA or eMASS
• Conduct vulnerability assessments and compliance scans (e.g., ACAS) and track remediation of findings and IAVM requirements
• Implement and validate security controls aligned with NIST 800-53, CNSSI 1253, and related DoD guidance
• Support system hardening, patching, and configuration management in compliance with STIGs for Linux, Windows, and network devices
• Monitor systems for security events and support incident response and risk mitigation activities
• Assess security impacts of system changes and support configuration control boards (CCBs)
• Collaborate with system engineers, administrators, and DevSecOps teams to integrate security throughout the system lifecycle
• Provide cybersecurity risk input to program leadership, Authorizing Officials (AOs), and stakeholders

Requirements

Required Qualifications:

• Bachelor's degree with 5+ years of experience (or equivalent experience)
• DoD 8570 IAT Level II or higher certification (e.g., Security+, CySA+, CISSP)
• Experience with RMF, A&A, POA&M, and ATO documentation (XACTA/eMASS)
• Hands-on vulnerability scanning and compliance tracking (ACAS, IAVM)
• Experience securing Linux and Windows systems, STIGs, patching, and system hardening
• Knowledge of NIST 800-series publications and incident response processes
• Strong analytical, communication, and collaboration skills
• US Citizenship required
• Active or current (within two years of active) Top Secret clearance with SCI eligibility

Desired Qualifications:

• Scripting or development experience (Python, Java, React)
• DevSecOps tools and pipeline experience
• Experience with Linux (Red Hat/CentOS), databases, web apps, or big data platforms
• Familiarity with Agile environments and tools (Jira, Confluence)
• Experience with NIST SP 800-171 and System Security Engineering (SSE)

Benefits

At Trinity Global Consulting (TGC), we value our employees and provide a comprehensive benefits package that includes:

• Medical, Dental & Vision Coverage – Coverage for eligible employees and family through CareFirst and VSP.
• Paid Time Off – PTO granted in accordance with contract requirements.
• Paid Holidays – 11 federal holidays observed annually.
• Disability & Life Insurance – Short-term/long-term disability, life insurance, and AD&D coverage included.
• 401(k) Retirement Plan – Competitive plan managed through Ameritas.
• Professional Training – Formal training provided as required, with additional learning opportunities based on role.

Role : Security Engineer

Location : Charlotte, Dallas (Hybrid)

Rate : $60/hr - $65/hr

Role Summary

Security Engineer with strong expertise in CNAPP (Wiz/Prisma), cloud security, and ETL data control validation.

Responsible for end-to-end validation of security controls across ETL pipelines and cloud workloads.

Ensure data integrity, control effectiveness, and audit compliance during large-scale data pipeline migration.

Key Responsibilities

Validate security and audit controls across ETL pipelines and data platforms.

Perform data reconciliation between source (Prisma) and target (Wiz) systems.

Ensure data completeness, accuracy, and integrity across pipelines.

Validate cloud security posture using Wiz (misconfigurations, vulnerabilities, IAM risks).

Validate ingestion of security data (EDR, IAM, cloud logs) into ETL pipelines.

Execute control testing across DEV, SIT, and UAT environments.

Identify control gaps and support remediation.

Ensure audit readiness and produce validation reports.

Support migration with parallel run validation and comparison.

Collaborate with data engineers, ETL developers, and security teams.

Required Skills & Experience

6–10 years of experience in security control validation, audit, or data security.

Strong understanding of ETL pipelines and data validation techniques.

Experience in data reconciliation and data quality validation.

Hands-on or strong exposure to CNAPP tools (Wiz preferred, Prisma Cloud).

Understanding of cloud security (AWS/Azure basics).

Knowledge of security findings: vulnerabilities, misconfigurations, IAM risks.

Security & Data Domain Knowledge

CNAPP concepts: CSPM, CWPP, CIEM.

Data integrity, completeness, and accuracy controls.

ETL pipeline security and data flow validation.

Security data pipelines (log ingestion, normalization, enrichment).

Audit and compliance frameworks.

Parallel run validation and control comparison.

Preferred Skills

Experience in banking or regulatory environments.

Exposure to Hadoop, Hive, MongoDB.

Experience in Prisma to Wiz migration.

Knowledge of OCSF or security data models.

Experience with automated validation (SQL/scripts).

Security Risk Advisors Intl., LLC (SRA) is offering a Cloud Security Engineer position. This role is responsible for designing, implementing, and maintaining security controls across SRA's multi-cloud environment, spanning Microsoft Azure/Entra ID, Google Cloud Platform (GCP), and Amazon Web Services (AWS). The Cloud Security Engineer will work closely with internal IT, security operations, and engineering teams to ensure cloud infrastructure is deployed and maintained in a secure, compliant, and resilient manner. 

Essential Functions 

• Design, implement, and maintain cloud security architectures across Azure/Entra ID, GCP, and AWS environments. 

• Administer and continuously improve cloud identity and access management (IAM) policies, roles, and privilege models across all three platforms. 

• Monitor cloud environments for misconfigurations, threats, and vulnerabilities using cloud-native and third-party security tooling (e.g., Defender for Cloud, Security Command Center, AWS Security Hub). 

• Operationalize cloud vulnerability and patch management processes, ensuring timely remediation of identified risks. 

• Implement and maintain Cloud Security Posture Management (CSPM) solutions to enforce security baselines and compliance standards. 

• Develop and enforce cloud security policies, standards, and guardrails (e.g., Azure Policy, GCP Organization Policies, AWS SCPs). 

• Collaborate with engineering and DevOps teams to embed security into CI/CD pipelines and infrastructure-as-code (IaC) workflows. 

• Conduct cloud security assessments and architecture reviews for new and existing environments. 

• Support incident response activities related to cloud infrastructure, including investigation, containment, and remediation. 

• Create and maintain technical documentation for cloud security architectures, configurations, and operational procedures. 

• Research and evaluate emerging cloud security technologies and provide recommendations for adoption. 

• Develop detection content and security analytics in SRA's internal SOC applicable to cloud environments. 

Requirements

Competencies 

In-depth understanding of: 

• Microsoft Azure and Entra ID, including conditional access, PIM, and Defender for Cloud 

• Google Cloud Platform (GCP) security services, including Security Command Center, IAM, and VPC Service Controls 

• Amazon Web Services (AWS) security services, including IAM, GuardDuty, Security Hub, and AWS Config 

• Cloud identity and access management principles and zero trust architecture 

Working knowledge of: 

• Cloud Security Posture Management (CSPM) and Cloud Workload Protection Platforms (CWPP) 

• Infrastructure-as-Code (IaC) tools such as Terraform, Bicep, or CloudFormation 

• Networking concepts as applied to cloud environments (VPCs, peering, private endpoints, firewalls) 

• SIEM and EDR technologies in cloud-integrated environments 

Experience with: 

• CI/CD pipeline security and DevSecOps practices 

• Organizing or supporting penetration testing, purple team exercises, or cloud-focused security assessments 

• Compliance frameworks relevant to cloud environments (e.g., CIS Benchmarks, NIST CSF, SOC 2) 

Moderate experience with: 

• Scripting and automation using Python, PowerShell, or Bash 

• Automation via tools such as Power Automate, Logic Apps, or cloud-native orchestration services 

Supervisory Responsibility  

None 

 

Work Environment    

This job operates on-site in a professional office environment or remotely as needed/required. This role routinely uses standard office equipment.  

  

Physical Demands  

The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. While performing the duties of this job, the employee is regularly required to talk and hear; use hands to finger, handle, or feel; and reach with hands and arms. The employee frequently is required to stand and walk. This is a largely sedentary role.  

Candidates with disabilities are encouraged to apply and email careers@sra.io with any questions. Reasonable accommodations may be made to enable disabled individuals to perform the essential functions of this role.  

  

Position Type/Expected Hours of Work    

This is a full-time position and hours of work and days are Monday through Friday 8:30am to 5pm. Occasional evening and weekend work may be required as job duties demand.  

   

Travel    

Less than 5%. 

Required Education and Experience 

• Punctuality and timely attendance to external client and internal stakeholder needs. 

• A bachelor's degree in Information Technology, Computer Science, or a similar field of study, or equivalent experience. 

• 3+ years of hands-on experience in cloud security engineering or a related role, with demonstrable experience across at least two of the three major cloud platforms (Azure, GCP, AWS). 

• Relevant cloud security certifications preferred (e.g., AZ-500, SC-100, Google PCSE, AWS Security Specialty). 

• A passion for learning about cloud security, emerging technologies, and threat landscapes. 

• Excellent verbal and written communication skills. 

• Strong time management and organizational skills. 

Other Duties   

Please note this job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee for this job. Duties, responsibilities, and activities may change at any time with or without notice.  

 

EEO Statement  

Security Risk Advisors is an Equal Opportunity Employer and prohibits discrimination or harassment of any kind. All employment decisions at SRA are based on business needs, job requirements, and individual qualifications, without regard to race, color, sex, sexual orientation, gender identity or expression, age, religion, national origin, disability, marital or family status, veteran status, medical condition, or any similar category protected under federal, state, or local laws.    

Benefits

Work with Experts: Robust internal training program, plus Company-paid external training. SRA recognizes the value of professional development for employees. Therefore, we encourage our employees to pursue continuing education and role-specific training. Every SRA employee is eligible to attend one training per year paid for by SRA. 

Mental Health Services: SRA has partnered with BetterHelp to provide SRA employees with free mental health support. BetterHelp connects individuals with licensed therapists for chat, video, and phone sessions. 

Medical / Dental / Other (regular full-time employees only) 

• Generous medical, dental, and vision benefits at different price points. 

• Company-paid disability and life insurance. 

• Company 401(k) plan including annual 3% safe harbor contribution. 

• Free patient advocacy service that helps find care providers and resolve insurance queries. 

• Free financial advising. 

• Generous parental leave, sick leave, and vacation policies. 

• Possibility to work remotely or with a flexible schedule when needed and approved. 

• Company-paid cell phone with discounted accessories. 

• 1-2-3 Give Program: 1. SRA will give $1,000 to a charity of your choice. 2. If you give an additional amount (up to $1,000), then 3. SRA will match that amount up to $1,000. 

• Other discounted, employee-paid benefits including pet insurance, legal support, and voluntary life insurance. 

 

SRA’s mission is to level up every day to protect our clients and their customers. This begins with our team members and their experience. SRA prides itself on maintaining a culture where team members have a shared sense of support and belonging, consistent with our It’s Personal company value. At SRA, we prioritize transparent career pathing, varied DEI programming and community groups, competitive benefits including mental health support, and an emphasis on a sustainable, healthy, and engaging work culture. SRA has twice been named a Best Place to Work by the Philadelphia Business Journal. 

These Essential Functions, Requirements, and Skills are guidelines. If you are a candidate who does not meet this exact job description but can demonstrate excellent organization, attention to detail, professionalism, flexibility, and self-direction in your professional background, we hope you apply. SRA values a diverse workplace and strongly encourages women, people of color, LGBTQ+ individuals, people with disabilities, members of ethnic minorities, and veterans to apply.  

Salary Range: $90k - 130k