Senior AI & Cloud Security Engineer - On-Site in MD

RCG

Suitland (MD)

On-site

USD 130,000 - 140,000

Full time

6 days ago

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Benefits offered by this job

Medical, Dental, Vision

401(k) with company match

Paid time off

Paid holidays

Job summary

RCG, Inc. in Suitland, MD, seeks an AI/Cybersecurity Solutions Engineer to join a federal SAE team. This senior role blends generative AI engineering, cloud security, and federal compliance to drive an agentic AI security platform and automation for NIST 800-53 workflows.

You will build RAG pipelines, evaluate foundation-model strategies, and integrate AWS security services to enable auditable security evidence. Strong Python, IaC, and Jira/Confluence skills are required.

Qualifications

Bachelor’s degree in computer science, cybersecurity, or related technical discipline.
4+ years of cloud security engineering experience.
2+ years of production experience with generative AI/LLM technologies.
2+ years of experience working with AWS security services.
2+ years of experience supporting federal compliance frameworks such as NIST, FedRAMP, and FISMA.
2+ years of active Jira and Confluence experience in an Agile or technical delivery environment.
Current DoD 8570-compliant certification specifically Security+.
Solid experience with Python development, including Python 3.11+, boto3, type hints, and robust error handling.
Experience with Amazon Bedrock, including agents, action groups, Knowledge Bases, guardrails, prompt engineering, and RAG.
Knowledge of AWS security technologies, including Security Hub, GuardDuty, Inspector, Config, IAM, CloudTrail, and OIDC.
Container security experience with ECR, ECS/EKS, image scanning, runtime monitoring, and hardening.
Knowledge of NIST SP 800-53 Rev. 5, control families, assessment procedures, and evidence requirements.
Experience with CI/CD and IaC technologies, including GitLab CI and CloudFormation and/or Terraform.
Git/version-control experience.
Demonstrated experience managing technical work in Jira and maintaining team documentation in Confluence.
Strong troubleshooting, analytical, and problem-solving skills.
Excellent written and verbal communication skills.

Responsibilities

Implement Amazon Bedrock agent action groups, including OpenAPI schemas and Python Lambda layers.
Develop Retrieval-Augmented Generation (RAG) pipelines using Bedrock Knowledge Bases with NIST, CIS benchmarks, SSPs, and threat intel.
Engineer prompts, guardrails, and input validation to improve AI security and resist prompt-injection.
Evaluate and evolve foundation-model strategies as platform requirements mature.
Develop AI-assisted capabilities supporting security assessment, remediation, hardening, alert triage, and compliance workflows.
Build automated NIST 800-53 control assessments and secure evidence collection.
Develop remediation and hardening automation across AWS services (S3, EC2, IAM, CloudTrail, ECS, EKS).
Integrate live data from AWS Security Hub, GuardDuty, Inspector, and Config for security analysis.
Support SLA logic, KEV correlation, risk enrichment, and remediation SLA tracking.
Support telemetry aggregation and integration with SIEM technologies (Microsoft Sentinel, AWS Security Lake).
Maintain GitLab CI/CD pipelines with linting, tests, security scans, builds, deployments.
Implement secure OIDC-based AWS authentication.
Develop and manage IaC using CloudFormation and/or Terraform with least-privilege IAM.
Support deployment and rollout verification across Kubernetes/EKS environments.
Maintain strong Git practices and traceability across requirements, code, and security evidence.
Take ownership of technical workstreams and collaborate with cybersecurity and engineering teams.