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Executive Ai Infrastructure Engineer Jobs in Virginia

The Josef Group

AI Infrastructure Engineer

Chantilly, VA · On-site

$110K - $144K/yr

AI Infrastructure Engineer Top Secret or TS/SCI is required to start $200K to $250K Chantilly, VA What You'll Do * Deploy and optimize self-hosted LLM inference servers (vLLM, Ollama, and similar)

Bigbear.ai

Cloud Infrastructure Engineer

Mclean, VA · On-site

$142K/yr

Residency All applicants must currently reside in the United States Overview Bigbear.ai is hiring Cloud Infrastructure Engineers to build and maintain the underlying government cloud infrastructure ...

BigBear.ai

Cloud Infrastructure Engineer

Mclean, VA · On-site

$57.25 - $76.50/hr

Residency All applicants must currently reside in the United States Overview Bigbear.ai is hiring Cloud Infrastructure Engineers to build and maintain the underlying government cloud infrastructure ...

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Executive Ai Infrastructure Engineer information

What is the difference between Executive Ai Infrastructure Engineer vs Data Engineer?

AspectExecutive Ai Infrastructure EngineerData Engineer
Required CredentialsBachelor's/Master's in Computer Science, AI, or related fields; certifications in cloud platforms and AI toolsBachelor's in Computer Science, Data Science, or related; certifications in data management and cloud platforms
Work EnvironmentDesigning and overseeing AI infrastructure, collaborating with AI teams, managing cloud resourcesBuilding data pipelines, managing databases, ensuring data quality and accessibility
Employer & Industry UsageTech companies, AI startups, enterprises deploying AI solutionsData-driven companies, analytics firms, tech organizations handling large datasets

The Executive Ai Infrastructure Engineer focuses on designing and managing AI-specific infrastructure, ensuring optimal performance for AI applications. In contrast, a Data Engineer primarily builds and maintains data pipelines and databases to support analytics and machine learning. Both roles require technical expertise and often collaborate, but their core responsibilities differ in scope and focus.

What are the most commonly searched types of Ai Infrastructure Engineer jobs in Virginia?

The most popular types of Ai Infrastructure Engineer jobs in Virginia are:

What cities in Virginia are hiring for Executive Ai Infrastructure Engineer jobs?

Cities in Virginia with the most Executive Ai Infrastructure Engineer job openings:

Executive Ai Infrastructure Engineer jobs near you

AI Infrastructure Engineer

The Josef Group

Chantilly, VA • On-site

$110K - $144K/yr

Full-time

Re-posted 20 hours ago

Job description

AI Infrastructure EngineerTop Secret or TS/SCI is required to start 
$200K to $250K 
Chantilly, VAWhat You'll Do
  • Deploy and optimize self-hosted LLM inference servers (vLLM, Ollama, and similar).
  • Containerize AI workloads using Docker and orchestrate production environments with Kubernetes, including GPU scheduling.
  • Build and maintain AI serving infrastructure, including gateways, load balancing, authentication, TLS, and rate limiting.
  • Optimize GPU utilization, memory management, quantization, batching, and capacity planning to balance performance and cost.
  • Develop and maintain CI/CD pipelines, observability, monitoring, and incident response processes.
What You'll Bring (Required)
  • Hands-on experience deploying and serving Large Language Models (LLMs) in production.
  • Strong experience with Docker and production Kubernetes environments, including GPU scheduling.
  • Deep understanding of self-hosted AI infrastructure, including model formats, quantization, GPU memory management, batching, and inference optimization.
  • Experience supporting production applications with networking, reverse proxies, load balancing, authentication, and TLS.
  • Proficiency with Linux administration and Python and/or Bash scripting.
  • Ownership mindset with the ability to operate and improve production AI infrastructure.
Nice to Have
  • Experience with CUDA, NVIDIA drivers, GPU Operators, or other GPU infrastructure technologies.
  • Experience with Infrastructure as Code (Terraform, Helm).
  • Familiarity with observability and monitoring tools such as Prometheus and Grafana.
  • Experience building Retrieval-Augmented Generation (RAG) pipelines and working with vector databases (pgvector, Qdrant, Weaviate).
  • Experience with LLM gateway tools such as LiteLLM.