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Remote Mobile Security Researcher Jobs in Washington

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 Responsibilities * Research and develop new approaches to AI red teaming, adversarial testing, security ...

New

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 Responsibilities * Research and develop new approaches to AI red teaming, adversarial testing, security ...

New

Ignite IT

Senior Network Security Engineer

Suitland, MD · Remote

$63 - $82.50/hr

Support remote-access VPN, site-to-site VPN, partner connectivity, cloud connectivity, mobile ... Hands-on experience with Cisco security technologies such as Cisco ASA, Firepower, FTD, FMC ...

Interrupt Labs

iOS Vulnerability Researcher

Arlington, VA · Remote

$59.50 - $82/hr

... security and reverse engineering on Apple platforms. The role: * You'll join our team looking to ... This is a remote role so the successful candidate can be based anywhere in the USA, or indeed the ...

Booz Allen Hamilton, Inc.

Mobile Trainer

Arlington, VA · On-site +1

$69K - $158K/yr

Remote Work: No Job Number: R0248536 Location: Arlington,VA,US Share job via: Share Mobile Trainer ... Applicants selected will be subject to a security investigation and may need to meet eligibility ...

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Remote Mobile Security Researcher information

What does a remote mobile security researcher do?

A Remote Mobile Security Researcher is a cybersecurity professional who specializes in identifying, analyzing, and mitigating security vulnerabilities in mobile devices and applications. Working remotely, they use various tools and techniques to test mobile operating systems like iOS and Android for weaknesses that could be exploited by hackers. Their responsibilities often include performing penetration tests, reverse engineering apps, and developing security solutions or patches. They also write detailed reports about their findings and may collaborate with development teams to improve mobile security. This role is crucial in helping organizations protect sensitive data and maintain user trust.

What are some common challenges faced by remote mobile security researchers, and how can they be addressed?

Remote Mobile Security Researchers often encounter challenges such as staying updated on rapidly evolving mobile threats and effectively collaborating with distributed teams. Working remotely can limit spontaneous knowledge sharing, so leveraging regular virtual meetings, secure collaboration tools, and participating in online security communities is crucial. Additionally, managing access to multiple devices and environments for testing requires strong organizational skills and adherence to strict security protocols. Proactively seeking continuous learning opportunities and maintaining clear communication with team members can help overcome these obstacles and lead to a successful research experience.

What are the key skills and qualifications needed to thrive as a remote mobile security researcher, and why are they important?

To thrive as a Remote Mobile Security Researcher, you need expertise in mobile operating systems, reverse engineering, vulnerability analysis, and a solid background in cybersecurity or computer science. Familiarity with tools like IDA Pro, Frida, Burp Suite, and certifications such as OSCP or GIAC Mobile Device Security is highly recommended. Strong problem-solving, analytical thinking, and self-motivation are crucial soft skills, especially when working independently and communicating findings remotely. These skills ensure effective identification and mitigation of mobile security threats, enabling organizations to protect sensitive data and maintain robust mobile app security.

What is the difference between Remote Mobile Security Researcher vs Mobile Security Analyst?

AspectRemote Mobile Security ResearcherMobile Security Analyst
CredentialsCertifications like CISSP, CEH, or OSCP often preferredSimilar certifications, often including CISSP, GIAC, or CEH
Work EnvironmentRemote or hybrid, focused on research and vulnerability discoveryTypically office-based or remote, focused on monitoring and incident response
Industry UsageUsed in cybersecurity firms, tech companies, and research labsCommon in enterprise security teams, government agencies, and corporations

The Remote Mobile Security Researcher primarily focuses on discovering vulnerabilities and analyzing mobile security threats through research, often working remotely. In contrast, a Mobile Security Analyst concentrates on monitoring, analyzing security incidents, and implementing protective measures. Both roles require similar certifications and work in cybersecurity but differ in their core responsibilities and work environments.

What are popular job titles related to Remote Mobile Security Researcher jobs in Washington?

For Remote Mobile Security Researcher jobs in Washington, the most frequently searched job titles are:

What job categories do people searching Remote Mobile Security Researcher jobs in Washington look for?

The top searched job categories for Remote Mobile Security Researcher jobs in Washington are:

What cities in Washington are hiring for Remote Mobile Security Researcher jobs?

Cities in Washington with the most Remote Mobile Security Researcher job openings:

Remote Mobile Security Researcher jobs near you
Infographic showing various Remote Mobile Security Researcher job openings in Washington as of August 2026, with employment types broken down into 86% Full Time, 11% Part Time, and 3% Contract. Highlights an 91% Physical, 2% Hybrid, and 7% Remote job distribution.

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.

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