AI Security Control Assessor (SCA)

SAIC is seeking Security Control Assessor/Representatives (SCA/Rs) to lead security control assessments across high-priority projects. Working at the intersection of cybersecurity engineering, cloud architecture, and DevSecOps prototyping, you will evaluate security controls for cutting-edge AI/LLM technologies across multiple classification levels. This position is ideal for a pragmatic cloud assessor or SCAR who excels in fast-paced DevSecOps environments, understands AWS cloud security, and is eager to shape the cybersecurity posture of next-generation DoD AI capabilities. 

 

This position will be based out of Arlington, VA. Additional responsibilities include:

 

Key Responsibilities

• Execute formal SCA/R duties.
• Lead security assessment efforts, establishing reusable security playbooks and assessment frameworks for rapid AI deployment into enterprise workflows.
• Evaluate technical control effectiveness across AWS cloud infrastructure, DevSecOps pipelines, microservices, containerized workloads, and GenAI/LLM application stacks.
• Partner directly with cybersecurity engineering and DevSecOps prototyping teams to integrate security controls early in the development lifecycle.
• Review, author, and maintain assessment packages—including System Security Plans (SSPs), Security Assessment Plans (SAPs), Security Assessment Reports (SARs), and POA&Ms—tailored to rapid prototyping and AI systems.
• Assess technical security risks specific to AI/LLM implementations, such as API exposure, vector database access controls, model integration surface area, and software supply chain dependencies.
• Support continuous monitoring (ConMon), technical risk evaluations, and cloud architecture reviews across multi-tenant, multi-classification environments.
• Coordinate with Authorizing Officials (AOs), program managers, and engineering leads to deliver decision-ready risk briefings and ATO recommendations.
• Provide technical input and oversight for cybersecurity engineering and penetration testing activities across prototype projects.

Qualifications

Required Qualifications

• US Citizen and Active Top Secret security clearance
• Bachelor's and Fourteen (14) or relevant years of experience in lieu of degree
• Current DoD 8570/8140 IAM Level II or Level III certification (e.g., Security+, CySA+, CISM, CISSP, CCISO, CAP/CISC)
• 3–5+ years of experience conducting security control assessments, compliance testing, or A&A/RMF activities for DoD or federal information systems
• Solid operational understanding of core AWS cloud services (EC2, S3, IAM, VPCs, Security Groups, Security Hub) and how security controls function within cloud-native and CI/CD pipeline environments.
• Strong working knowledge of NIST SP 800-53 (Rev. 4/5), NIST SP 800-37 (RMF), DoD Cloud Computing SRG, and FedRAMP baselines.
• Demonstrated experience writing and evaluating core RMF artifacts (SSPs, SAPs, SARs, POA&Ms)
• Exceptional written and verbal communication skills, with the ability to articulate technical risk clearly to executive stakeholders, Authorizing Officials, and engineering teams.
• Hands-on experience navigating government GRC repositories, such as eMASS or XACTA.

 

Desired Qualifications

• Hands-on experience mapping security controls to the NIST AI Risk Management Framework (AI RMF), the OWASP Top 10 for LLM Applications, or the DoD Responsible AI (RAI) Guidelines.
• Familiarity evaluating secure design patterns for autonomous AI Agents (e.g., tool-calling permissions, sandboxing agent execution environments, prompt boundaries, and ReAct/LangGraph architectures).
• Experience assessing cloud-managed AI ecosystems and foundation model platforms (e.g., AWS Bedrock, AWS SageMaker, Hugging Face Enterprise, or self-hosted open-source models).
• Understanding of data protection, access controls, and boundary security for RAG pipelines and vector databases (e.g., OpenSearch Vector Engine, Pinecone, Milvus, or PostgreSQL pgvector).
• Familiarity evaluating risks unique to LLMs—including prompt injection, data poisoning, model inversion, insecure output handling, and open-source supply chain vulnerabilities in AI libraries (PyTorch, LangChain, LlamaIndex).
• Exposure to LLM guardrail platforms, evaluation frameworks, or AI security tools (e.g., Promptfoo, Garak, Giskard, NeMo Guardrails) used to test model robustness and output safety.
• Experience with cATO methodologies, Infrastructure as Code (IaC) templates (Terraform, CloudFormation), and container security (AWS EKS/ECS, Docker).
• Active AWS Certifications (e.g., AWS Certified Security – Specialty or AWS Certified Solutions Architect).
• Background or familiarity with offensive security, penetration testing

SAIC® is a premier mission integrator focused on advancing the power of technology and innovation to serve and protect our world. Our robust portfolio of offerings across the defense, space, intelligence, and civilian markets includes secure high-end solutions in mission IT, enterprise IT, engineering services, and professional services. We integrate emerging technology, rapidly and securely, into mission critical operations that modernize and enable critical national imperatives.