Systems Engineer - AI Integration - TS/SCI
Role details
Job location
Tech stack
Job description
Own your opportunity to serve as a critical component of our nation's safety and security. Make an impact by using your expertise to protect our country from threats., 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., * 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.
Requirements
- Education: Bachelor's degree in Computer Science, Information Systems, Engineering, Cybersecurity, or a related field; equivalent experience also considered.
- Experience: 8+ years
- Required technical skills:
- 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
- Additional Requirements:
- 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
- Security clearance level: TS/SCI with Polygraph
- Preferred Qualifications
- 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
- Location: Herndon, VA - customer site
OWN YOUR OPPORTUNITY Explore a career in data science and engineering at GDIT and you'll find endless opportunities to grow alongside colleagues who share your determination for solving complex data challenges.
#OpportunityOwned #GDITCareers #WeAreGDIT #JET #GDITEnhanced2026 #VA_2026Alumni
Work Requirements
Years of Experience
8 + years of related experience
- may vary based on technical training, certification(s), or degree Certification
AWS Certified AI Practitioner | Amazon Web Services (AWS) - Amazon Web Services (AWS) Travel Required
Benefits & conditions
The likely salary range for this position is $187,000 - $253,000. This is not, however, a guarantee of compensation or salary. Rather, salary will be set based on experience, geographic location and possibly contractual requirements and could fall outside of this range.