Systems Engineer - AI Integration - TS/SCI with Polygraph

General Dynamics Information TechnologyHerndon, VA
$187,000 - $253,000Onsite

About The Position

Bring your leading-edge technology expertise and thirst for knowledge to GDIT's premier cybersecurity contract! We are looking for an innovative, forward-thinking engineer with experience in frontier technologies like AI/ML, Automation, and Cloud/DevOps. You will be in a role with a good deal of latitude to propose improved methods, implement new processes, and research/integrate AI-centric solutions to accelerate AI-driven cybersecurity.

Requirements

  • Bachelor’s degree in Computer Science, Information Systems, Engineering, Cybersecurity, or a related field; equivalent experience also considered.
  • 8+ years of related experience
  • Hands-on experience deploying or integrating AI/ML platforms, services, or tooling into operational systems.
  • Strong background in systems engineering, infrastructure engineering, solutions architecture, or related technical roles in secure environments including:
  • Linux administration (RHEL, CentOS, Ubuntu)
  • Networking fundamentals including TCP/IP, DNS, VPNs, firewalls, routing, proxies, and load balancing
  • Containerization and orchestration technologies such as Docker and Kubernetes
  • Cloud infrastructure, primarily AWS, including IAM, networking, and security services
  • Infrastructure and configuration management tools such as Terraform, CloudFormation, or Ansible
  • Scripting or development experience with Python, Bash, PowerShell, Go, or similar languages
  • Experience with AI/ML infrastructure such as:
  • Model serving platforms and APIs (MLflow, SageMaker, TorchServe, Vertex AI, Azure ML, custom REST/gRPC services)
  • Logging and telemetry pipelines
  • Relational, NoSQL, object storage, or vector database technologies
  • CI/CD, Git workflows, artifact management, and automated deployment pipelines
  • Understanding of core cybersecurity concepts, including:
  • Authentication and authorization (SSO, SAML, OIDC, OAuth, RBAC)
  • Encryption, certificates, and key management
  • Security monitoring and SIEM/SOAR integrations
  • Strong troubleshooting and problem-solving skills
  • Ability to translate operational and security requirements into technical solutions
  • Comfortable working in fast-paced, highly collaborative environments
  • Strong written and verbal communication skills
  • TS/SCI with Polygraph clearance

Nice To Haves

  • Experience supporting AI-driven cybersecurity use cases such as threat detection, anomaly detection, UEBA, or automated incident response
  • Experience integrating hosted or on-prem LLM platforms
  • Familiarity with retrieval-augmented generation (RAG), prompt engineering, and associated data pipelines
  • Experience with cybersecurity platforms such as Splunk, Elastic, QRadar, EDR/XDR, IDS/IPS, or SOAR technologies
  • Experience operating in regulated, mission-critical, or high-security environments

Responsibilities

  • Design and implement architectures that integrate AI/ML platforms, model-serving infrastructure, vector databases, and MLOps tooling into enterprise environments.
  • Design, deploy, and maintain AI/ML platforms and supporting infrastructure across cloud, hybrid, and on-prem environments.
  • Integrate AI services with existing enterprise systems, including SIEM/SOAR platforms, APIs, ticketing systems, and operational data sources.
  • Build and maintain secure, scalable pipelines for AI workloads, telemetry, logs, and other structured or unstructured data.
  • Automate infrastructure deployment, configuration management, and operational workflows using tools such as Terraform and Ansible.
  • Support Kubernetes- and container-based environments used for AI applications and model serving.
  • Work closely with cybersecurity teams to implement hardening, access controls, monitoring, and other security requirements for AI systems.
  • Participate in threat modeling, risk assessments, and ATO-related activities for AI infrastructure and integrations.
  • Monitor and troubleshoot issues across systems, networks, applications, and cloud environments.
  • Develop operational documentation including architecture diagrams, runbooks, SOPs, and integration documentation.
  • Advise technical leadership and mission stakeholders on implementation approaches, tradeoffs, and operational risks related to AI technologies.
  • Mentor junior engineers and contribute to improving engineering and operational practices across the team.

Benefits

  • Variety of medical plan options, some with Health Savings Accounts
  • Dental plan options
  • Vision plan
  • 401(k) plan offering the ability to contribute both pre and post-tax dollars up to the IRS annual limits and receive a company match.
  • Full flex work weeks where possible
  • Variety of paid time off plans, including vacation, sick and personal time, holidays, paid parental, military, bereavement and jury duty leave.
  • Short and long-term disability benefits
  • Life, accidental death and dismemberment, personal accident, critical illness and business travel and accident insurance are provided or available.
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