Senior Systems Engineer

VTG LLC
Chantilly, VA, United States
4 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Amazon Web Services Software Applications Systems Engineering Microsoft Azure Cloud Computing Communications Protocols Cyber Security Continuous Integration Data Governance Microprocessors
+18 more
Distributed Computing Environment Distributed Systems Machine Learning Zero Trust Network Access Software Engineering Systems Architecture Systems Integration Google Cloud Enterprise Software Applications Large Language Models Software Security Containerization Kubernetes Low Latency Machine Learning Operations Cyber Warfare Data Pipelines Docker

Job description

We are seeking an experienced Senior AI/ML Systems Engineer to design, integrate, deploy, and maintain enterprise-grade AI-enabled systems supporting cyber operations. This role combines systems engineering, software development, cybersecurity, cloud infrastructure, and AI/LLM integration to modernize existing architectures and deliver scalable, secure technical solutions.

What will you do?

  • Design, build, deploy, and maintain enterprise-grade software applications and systems.
  • Integrate modern AI and Large Language Model (LLM) capabilities into existing legacy architectures, APIs, and enterprise systems.
  • Design scalable system architectures capable of supporting AI/ML model inference, training, and distributed processing.
  • Develop and maintain containerized applications using Docker and Kubernetes.
  • Design and support Kubernetes clusters and other orchestration environments for highly available and scalable workloads.
  • Support technical solutions for offensive and/or defensive cyber operations.
  • Implement secure system architectures incorporating Zero Trust principles, secure API gateways, and data governance controls.
  • Design and support cloud infrastructure within AWS, Azure, and/or Google Cloud Platform (GCP).
  • Optimize cloud infrastructure for AI/ML workloads utilizing GPU instances, virtual CPUs, high-speed networking, and distributed computing resources.
  • Design and support data pipelines used for AI/ML model training and inference.
  • Apply network engineering principles, low-latency communication protocols, and system security practices to complex technical environments.
  • Collaborate with software engineers, cybersecurity professionals, cloud engineers, data scientists, and other technical teams.
  • Translate complex customer and mission requirements into scalable system architectures and technical designs.
  • Provide technical guidance and mentorship to junior engineers.
  • Support automation, software delivery, and deployment through CI/CD and MLOps/LLMOps practices.

Requirements

  • Active TS/SCI with Polygraph
  • BS degree and 11-15 years of relevant experience
  • 7+ years of experience in software development or systems engineering, including building, deploying, and maintaining enterprise-grade applications.
  • 5+ years of experience supporting offensive and/or defensive cyber operations.
  • Demonstrated experience integrating AI and Large Language Models (LLMs) into existing applications, APIs, legacy architectures, or enterprise systems.
  • Hands-on experience with containerization and orchestration technologies, including:
  • Docker
  • Kubernetes
  • Cluster management
  • Knowledge of Zero Trust architecture, secure API gateways, and data governance requirements associated with AI/LLM deployments.
  • Knowledge of cloud infrastructure platforms such as AWS, Azure, or GCP.
  • Understanding of cloud infrastructure supporting AI/ML and distributed workloads, including GPU instances, vCPUs, and high-speed networking.
  • Knowledge of network engineering fundamentals and low-latency protocols.
  • Understanding of system and application security principles.
  • Knowledge of data pipeline architectures supporting AI/ML model inference and training.
  • Demonstrated ability to translate complex customer requirements into scalable technical solutions and system designs.
  • Strong collaboration and communication skills with the ability to work across multidisciplinary technical teams.
  • Experience providing technical guidance or mentorship to junior engineers.

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