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Remote Infrastructure Management Jobs in Virginia

Air

Senior AI Engineer, Security Infrastructure

Arlington, VA · On-site +1

$124K - $169K/yr

... Remote for those outside of those cities. This role may require up to 25% travel Scope of ... Implement security controls around identity and access management, secrets, network isolation ...

New

Orion ICS LLC

Remote Recruiter

Virginia Beach, VA · On-site +1

... infrastructure, automation, engineering, and commercial functions. * Provide market intelligence, compensation trends, and talent availability insights to hiring managers and business leaders.

FusionTek

Client Relationship Manager - DC

Arlington, VA · On-site +1

$85K - $100K/yr

Our innovative team is passionate about IT infrastructure management for small- to mid-sized ... This position is listed as Hybrid - primarily remote with occasional travel to client meetings ...

CORAS

Cloud Infrastructure Engineer

Mclean, VA · Remote

$56.25 - $75.25/hr

... manage risk, compliance, and security operations in highly regulated environments. We're looking ... AWS certifications or relevant technical certifications Work Environment This is a fully remote ...

Coras

Cloud Infrastructure Engineer

Mclean, VA · On-site +1

$128K - $145K/yr

... manage risk, compliance, and security operations in highly regulated environments. We're looking ... AWS certifications or relevant technical certifications Work Environment This is a fully remote ...

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Showing results 21-40

All JobsInfrastructure Management JobsRemote Infrastructure Management JobsRemote Infrastructure Management Jobs in Virginia

Remote Infrastructure Management information

See Virginia salary details

$79.8K

$152.7K

$196.3K

How much do remote infrastructure management jobs pay per year?

As of Sep 6, 2026, the average yearly pay for remote infrastructure management in Virginia is $152,707.00, according to ZipRecruiter salary data. Most workers in this role earn between $112,000.00 and $195,300.00 per year, depending on experience, location, and employer.

What is remote infrastructure management?

A Remote Infrastructure Management (RIM) job involves monitoring, maintaining, and supporting an organization's IT infrastructure remotely. This includes servers, networks, databases, storage, and security systems to ensure optimal performance and security. Professionals in this role use remote monitoring tools to detect and resolve issues, perform regular maintenance, and implement infrastructure upgrades. RIM helps businesses reduce costs, improve efficiency, and ensure 24/7 IT system availability without requiring an on-site team.

What does a typical day look like for someone in remote infrastructure management?

A typical day in Remote Infrastructure Management involves monitoring system performance, responding to alerts, performing routine maintenance, and troubleshooting infrastructure issues as they arise. You might also collaborate with other IT teams to plan upgrades, patch vulnerabilities, and implement new technologies. Remote work often requires proactive communication and regular check-ins to align with team goals. While core responsibilities remain technical, adapting to rapidly changing problems and ensuring the stability of digital environments are at the heart of the role.

What are the key skills and qualifications needed to thrive in remote infrastructure management?

To thrive in Remote Infrastructure Management, you need expertise in network administration, server management, cloud platforms, and a solid understanding of IT security, generally supported by a degree in computer science or related certifications like CCNA, AWS, or Azure. Familiarity with monitoring tools like Nagios, virtualization platforms like VMware, and automation scripts is highly valuable. Strong problem-solving, communication, and time-management skills ensure effective remote collaboration and swift issue resolution. These competencies are essential to maintain uptime, secure data integrity, and support seamless operations across distributed environments.

What are popular job titles related to Remote Infrastructure Management jobs in Virginia?

For Remote Infrastructure Management jobs in Virginia, the most frequently searched job titles are:

What job categories do people searching Remote Infrastructure Management jobs in Virginia look for?

The top searched job categories for Remote Infrastructure Management jobs in Virginia are:

What cities in Virginia are hiring for Remote Infrastructure Management jobs?

Cities in Virginia with the most Remote Infrastructure Management job openings:

Remote Infrastructure Management jobs near you
Infographic showing various Remote Infrastructure Management job openings in Virginia as of August 2026, with employment types broken down into 89% Full Time, 5% Part Time, and 6% Contract. Highlights an 100% Remote job distribution, with an average salary of $152,707 per year, or $73.4 per hour.

Senior AI Engineer, Security Infrastructure

Air

Arlington, VA • On-site, Remote

$124K - $169K/yr

Full-time

Posted 2 days ago

New

Job description

Company Description
Air is the leader in Enterprise Readiness. Our mission is to establish readiness as a real-time condition that is continuously achieved. Today, a dangerous Readiness Gap exists between what the front line needs and what is delivered. Our AI-native platform, Air Enterprise Readiness, aligns development, production, delivery, and sustainment into one coordinated execution system for government agencies and industrial suppliers. By revealing true capacity, exposing real constraints, coordinating resources, and executing at the speed of operational demands, the front line gets what it needs to succeed.
Job Description

We are seeking an experienced Senior AI Engineer specializing in AI security to join our Agentic AI team as we scale our agentic capabilities across all levels of the U.S. government.
Over the past year, we have seen rapid adoption of our AI agent, Ace. As agents gain access to increasingly powerful tools, data, and workflows, securing these systems presents a fundamentally different set of challenges from securing traditional software.

AI security is not a solved problem. This role sits at the intersection of applied AI research, offensive security, and production systems engineering. You will identify how agentic systems can fail or be exploited, develop new approaches for detecting and mitigating those failures, and build the infrastructure necessary to deploy capable AI agents securely in adversarial environments.

You will work directly with the engineers building our agent runtime, evaluation infrastructure, tools, and production AI systems. The goal is not simply to identify vulnerabilities - it is to turn what we learn into durable security architecture, automated evaluations, and engineering primitives that make our entire AI platform more secure.

This role is a full-time position located out of our office in Pittsburgh, PA or Arlington, VA and Remote for those outside of those cities. 

This role may require up to 25% travel

Scope of Responsibilities
  • Research and develop new approaches to AI red teaming, adversarial testing, security evaluation, and robust inference.
  • Threat model agentic AI architectures, identifying trust boundaries, attack surfaces, privileged capabilities, and potential failure modes.
  • Design adversarial evaluations targeting threats such as prompt injection, indirect prompt injection, tool abuse, privilege escalation, data exfiltration, context or memory poisoning, and unintended agent behavior.
  • Build automated security evaluation and regression frameworks that continuously test agents, models, tools, and infrastructure against known and emerging attacks.
  • Translate successful attacks and research findings into production mitigations, architectural improvements, and reusable security controls.
  • Design secure execution environments for AI agents interacting with tools, code, data, and external systems.
  • Build and harden sandboxing and isolation mechanisms for executing agent-generated or otherwise untrusted workloads.
  • Design capability boundaries, permission models, and least-privilege access controls for agent tools and services.
  • Develop scalable AI infrastructure and services supporting secure model inference and agent execution.
  • Own and improve production infrastructure across Kubernetes, AWS, networking, storage, and compute.
  • Implement security controls around identity and access management, secrets, network isolation, containers, and service-to-service communication.
  • Build scalable APIs, internal platform services, and infrastructure tooling that improve developer productivity, system reliability, and security.
  • Improve observability across AI systems through structured logging, metrics, distributed tracing, dashboards, security telemetry, and automated alerting.
  • Investigate complex production and security failures across models, agents, distributed systems, and infrastructure.
  • Optimize performance, latency, and infrastructure cost while maintaining strong reliability and security guarantees.
  • Stay current with emerging attacks against LLMs and agentic systems and rapidly translate relevant research into practical evaluations and defenses.
Qualifications
  • U.S. Citizenship is required
Required Skills: 
  • 5+ years of experience building production software, backend infrastructure, distributed systems, security systems, or AI/ML infrastructure.
  • Bachelor's, Master's, or Doctorate in Computer Science, Computer Engineering, Cybersecurity, Data Science, or a related technical field, or equivalent practical experience.
  • Demonstrated experience in AI red teaming, adversarial machine learning, offensive security, systems security, or related security research.
  • Experience evaluating AI systems beyond basic direct prompt injection attacks.
  • Strong understanding of how modern LLM and agentic systems operate, including model inference, context management, tool use, retrieval, and multi-step agent execution.
  • Strong intuition for how AI systems can fail when exposed to adversarial users, untrusted data, external tools, and complex production environments.
  • Experience threat modeling complex systems and translating identified risks into concrete engineering controls.
  • Strong programming experience in Python and experience building production-quality software.
  • Experience operating production services on Kubernetes and cloud platforms such as AWS, GCP, or Azure.
  • Strong understanding of networking, distributed systems, containers, service orchestration, and scalable architectures.
  • Experience designing APIs, services, asynchronous systems, and event-driven architectures.
  • Comfortable debugging failures that span application code, AI models, distributed systems, and infrastructure.
  • Able to move between research and engineering: reading new research, developing an attack or defense, validating it experimentally, and turning the result into a production system.
  • Passionate about building secure AI systems and proactively defending against novel attack vectors.

Desired Skills: 

  • Experience designing or securing AI agent runtimes and tool-execution environments.
  • Experience building secure code execution sandboxes, container isolation, microVMs, or other mechanisms for running untrusted workloads.
  • Experience with cloud security, infrastructure hardening, IAM, secrets management, network isolation, and zero-trust architectures.
  • Experience with offensive security, penetration testing, vulnerability research, or exploit development.
  • Experience developing automated adversarial evaluations or integrating security evaluations into CI/CD pipelines.
  • Experience with adversarial machine learning, model robustness, or inference-time defenses.
  • Familiarity with AI security frameworks and threat taxonomies such as MITRE ATLAS, OWASP guidance for LLM/GenAI applications, or the NIST AI Risk Management Framework.
  • Experience securing RAG systems, vector stores, model gateways, or other components of modern AI infrastructure.
  • Experience with software supply-chain security and securing model, dependency, and container artifacts.
  • Experience working in government, defense, or other high-security environments.
We firmly believe that past performance is the best indicator of future performance.  If you thrive while building solutions to complex problems, are a self-starter, and are passionate about making an impact in global security, we're eager to hear from you.
 
Air is an Equal Opportunity Employer.  All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans status or any other characteristic protected by law.